Wars, sanctions, supply chain disruptions, changing trade agreements, economic nationalism, cybersecurity threats and increasingly competitive relationships between major economies have moved from the pages of international news into boardrooms and budget meetings.

For Canadian tech companies, there’s an additional layer; the increasingly complicated relationship between Canada and the United States.

The temptation is to think, “We are a software company, tariffs are somebody else’s problem.” But unfortunately, it is not quite that simple.

Geopolitical Risk is Now Business Risk

The World Economic Forum’s Global Risks Report 2026 puts the issue rather bluntly. Geoeconomic confrontation is ranked as the top global risk for 2026, with interstate conflict, societal polarization, misinformation and cyber insecurity also among the leading concerns. Half of the more than 1,300 experts surveyed expect the next two years to be turbulent or stormy.

That matters to technology leaders because modern businesses are built on interconnected systems.

Your application may run in one country, use cloud infrastructure from another, depend on an open-source project maintained somewhere else, process data across several jurisdictions and serve customers on both sides of a border.

The code may be Canadian.

But the dependency graph is decidedly international.

This dependency creates several areas where geopolitical instability can become an IT issue.

1. Supply chain resilience

Software has made business more digital, but it has not made business independent of physical supply chains.

Servers, networking equipment, laptops, storage, semiconductors and other technology infrastructure still move through international supply chains. So do many of the components that support the digital economy.

The World Economic Forum identifies geopolitical confrontation and military conflict as major threats to global supply chains.

For technology leaders, this raises practical questions:

• How dependent are we on a single hardware supplier?
• What happens if a critical component becomes unavailable?
• How quickly can we replace a technology vendor?
• Where is our data stored, really?
• Which countries are involved in our technology supply chain?
• What happens if a supplier becomes subject to sanctions or export restrictions?

These are no longer hypothetical questions reserved for multinational corporations.

These now belong in technology risk assessments.

2. Cybersecurity is becoming geopolitical

Cybersecurity has always been a business concern. However, geopolitical instability makes it considerably more complicated.

Canada’s National Cyber Threat Assessment warns that state-sponsored cyber operations against Canada and its allies extend beyond traditional espionage. Threat actors are increasingly attempting disruptive activities, including denial of service, data theft, data manipulation and attacks designed to support military or political objectives.

The assessment specifically identifies Russia, China and Iran as significant state-sponsored cyber threats to Canada, while warning that Canadian organizations can also be exposed through supply chain compromises and cloud-based services.

That means cybersecurity strategy cannot simply be about protecting the corporate network anymore.

Technology leaders should also understand:

• Third-party software exposure
• Cloud and SaaS concentration risk
• Software supply chain vulnerabilities
• Identity and credential management
• Disaster recovery dependencies
• Vendor access
• Data sovereignty
• Business continuity if a critical technology provider becomes unavailable

In other words, the geopolitical environment is making the IT architecture itself part of an organization’s risk profile.

3. Then there is the Canada-US trade relationship

The Canada-US relationship has been remarkably integrated for decades. That integration is now being tested.

As of August 22, 2026, the United States imposed a 50% tariff on $27.6 billion of Canadian goods. Canada subsequently announced counter-tariffs of 15%, 25% and 50% on selected US products, covering approximately $27.6 billion of US products effective September 8, with targeted measures including electronics, appliances, steel and aluminum, among other categories.

The good news for software companies is that this does not mean every Canadian software service suddenly carries a 50% tariff.

The bad news is that the impact of trade friction does not stop at the customs border.

Reuters reported on September 3 that Canada’s trade surplus fell sharply in July, while the share of Canadian exports going to the United States declined to 66.35%, compared with 69.39% in June. Exports to non-US markets increased 7.4% during the month.

That means your technology customers may be changing their behaviour even if your software itself is not directly subject to a tariff.

They may delay projects.

They may reduce discretionary spending.

They may rethink expansion.

They may demand greater efficiency from existing systems.

And, interestingly, that last point can create an opportunity for technology companies.

4. Uncertainty changes technology budgets

When economic conditions become unpredictable, organizations tend to look much harder at technology spending.

That does not necessarily mean technology budgets disappear. It often means the standard for approving spending changes.

“Wouldn’t it be nice?” becomes“What problem does this solve?”

“Let’s replace it” becomes“Can we modernize it incrementally?”

“Let’s buy another platform” becomes “Can we get more value from what we already own?”

Statistics Canada found that businesses responding to tariff pressures were considering strategies including alternative suppliers, domestic sourcing, delaying major expenditures and investing in technology improvements. These are important distinctions.

Uncertainty can suppress technology spending, but it can also increase demand for technology that improves efficiency, resilience and control. For business and technology leaders, this is where modernization becomes strategic rather than cosmetic.

If a legacy application is expensive to maintain but essential to the business, replacing it may not be financially realistic during an uncertain economic period. Modernizing the user interface, improving integrations, exposing APIs, cleaning up data, improving documentation or stabilizing the underlying architecture may provide a much better return.

Sometimes the smartest technology investment is not the newest technology; sometimes it’s making the technology you already have more resilient.

5. Canadian technology businesses need to think beyond the US market

There is another side to this conversation.

Canada’s economy has historically benefited enormously from access to the United States. But geopolitical and trade uncertainty is encouraging Canadian organizations to diversify.

Global Affairs Canada’s State of Trade 2026 reports that Canadian goods trade with the United States declined in 2025 amid tariffs and trade policy uncertainty, while Canada’s non-US export share reached its highest level in more than four decades.

For technology businesses, diversification may be considerably easier than it is for manufacturers.

Canada’s digitally enabled services represented approximately 13% of Canada’s exports in 2025 and have grown substantially faster than goods exports since 2010. Export Development Canada also identifies computer services, information services and research and development as areas where Canada has competitive advantages.

That is an opportunity.

Canadian technology companies can sell expertise internationally without necessarily moving factories, inventory or physical infrastructure across borders.

But diversification requires technology businesses to ask whether their own operations are ready for it.

• Can your systems support multiple currencies?
• Can your contracts accommodate different jurisdictions?
• Can your data architecture support different privacy requirements?
• Can your team support customers in different time zones?
• Can your infrastructure be moved if regulatory requirements change?
• Can your business operate if one major market suddenly becomes less predictable?

These are technology architecture questions, but they are also business strategy questions.

6. What does this mean for technology employees?

This is perhaps the most overlooked part of the conversation.

Geopolitical uncertainty eventually reaches people.

When customers delay spending, businesses may slow hiring. When costs rise, companies may scrutinize compensation and operating expenses. When projects are delayed, technology teams can find themselves managing larger backlogs with fewer resources.

Statistics Canada reported that recruiting skilled employees remained one of the leading obstacles identified by Canadian businesses in the third quarter of 2026, with 25.2% identifying it as an expected obstacle.

This creates a strange contradiction. Organizations may become more cautious about technology spending while simultaneously needing highly skilled technology professionals more than ever.

The answer may increasingly be flexibility.

Instead of attempting to hire every specialized skill permanently, organizations can use a combination of internal teams, specialized consultants, staff augmentation and strategic software development partners.

These approaches can help businesses maintain critical systems and continue modernization projects without committing to a permanent expansion of every capability.

It can also help technology employees avoid the familiar cycle of being asked to maintain yesterday’s systems while simultaneously being expected to build tomorrows.

7. Resilience is becoming a technology strategy

For years, resilience was often treated as a disaster recovery conversation.

Backups, redundancy, recovery time objectives, business continuity; these things still matter. But resilience now needs to include geopolitical resilience.

Business leaders should understand where their critical technology dependencies live, who controls them, how replaceable they are and what happens if access changes unexpectedly.

That means conducting regular reviews or audits of:

• Critical software and infrastructure dependencies
• Vendor concentration
• Cloud providers and regions
• Data residency
• Cybersecurity exposure
• Software supply chains
• Legacy system dependencies
• Disaster recovery capabilities
• Documentation and institutional knowledge
• Internal technical skills
• External technical support options

The objective is not to eliminate every risk, that’s impossible.

The objective is to understand which risks could stop the business and make sure there is a plan for them.

The Opportunity Hidden Inside the Uncertainty

There is a tendency to talk about geopolitics as if businesses are simply passengers on a train heading somewhere unpleasant.

That is not entirely true.

Businesses still have choices, they can:

• Diversify suppliers
• Modernize strategically
• Strengthen cybersecurity
• Reduce unnecessary technical debt
• Document critical systems
• Build flexible technology architectures
• Invest in their people
• Diversify markets

And they can stop treating technology as a collection of projects and start treating it as part of the organization’s resilience strategy.

Canada’s current trade situation is a useful reminder that stability should never be confused with permanence. For decades, Canadian businesses could reasonably assume that the Canada-US economic relationship would remain predictable. Today, that assumption requires more qualification.

The same lesson applies to technology.

The system that has always worked may continue to work, the vendor you’ve always used may remain available, the supply chain you’ve always relied on may remain intact.

Strong technology leadership is not about predicting exactly what happens next; it’s about making sure the business can adapt when something changes. That is the real value of resilient software architecture, and in an increasingly unpredictable world, adaptability may be the most valuable asset a business can own.

At STEP Software, we help businesses assess, stabilize and modernize the software they already depend on, while building technology strategies that support what comes next. Drop us a line if you are feeling the pressure and need guidance on how to keep your tech stack flexible and resilient.

The post Tariffs as a Weapon: Geopolitics Has Entered IT first appeared on STEP Software.

Parton became one of the most recognizable figures in music and entertainment while building a business empire and an extraordinary philanthropic legacy. Curry became an international cultural icon through The Rocky Horror Picture Show, and then spent decades championing for the LGBTQ+ community while navigating a career in theatre, film, television, music and voice acting.

Both were iconic champions of diversity and pushing the boundaries of societal norms. They are proof that some of our most powerful leaders are gentle and compassionate humanitarians who also made walking on six-inch platform stilettos look easy.

Their deaths are sad, but their careers offer something constructive for the technology industry to think about.

How do we stay relevant when the world around us keeps changing?

This question applies to software systems, to technology organizations and perhaps most importantly, it applies to the humans building and maintaining them.

Technology Has Legacy Systems. People Have Institutional Knowledge.

The technology industry spends a lot of time worrying about legacy software.

And for good reason.

Legacy applications can become difficult to maintain, expensive to modify and increasingly dependent on technologies that fewer people know well.

But there is another form of legacy that organizations often overlook: institutional knowledge.

A senior developer may know why a particular database table was designed in a seemingly bizarre way. An architect may remember the reason an application was split into three services. A systems administrator may know which seemingly unrelated server is responsible for keeping an ancient integration alive. A business analyst may be the only person who understands why a particular workflow exists in the first place.

This knowledge is incredibly valuable but, it is also incredibly vulnerable.

When an experienced technology professional retires, changes careers or leaves an organization, the company may discover that years of operational knowledge were never documented.

The software remains while the knowledge disappears.

Why Succession Planning Belongs in IT

Succession planning is sometimes treated as an HR exercise, but in technology it should also be treated as risk management.

Consider a critical legacy application that only one senior developer understands.

What happens when that developer retires?

The organization may hire someone to replace them. But, hiring someone who understands the technology is not necessarily the same as hiring someone who understands the history of the application, the business rules embedded within it and the reasons behind its architecture.

This is one reason legacy software modernization should include more than a technology assessment.

It should include a knowledge assessment:

• Who understands the system?
• Where is the documentation?
• Which processes depend on individual knowledge?
• Which integrations are effectively dependent on one person’s memory?
• What would happen if that person were unavailable tomorrow?

These are all uncomfortable questions. They are also considerably cheaper to answer before there is an emergency.

Dolly Didn’t Become Relevant by Staying the Same

Parton’s career is a nearly perfect example of reinvention.

She became successful as a songwriter and performer, then expanded into film and television, business, tourism and philanthropy.

Reuters reports that she wrote approximately 3,000 songs, sold more than 100 million albums and built a business empire that included a major ownership stake in Dollywood. It also highlights her decision to retain rights to her music catalogue, allowing work created earlier in her career to continue generating value.

There is a useful technology lesson hiding in her career.

Don’t abandon the things that made you successful. Build on them.

A technology professional’s existing knowledge is an asset.

The goal isn’t to become a completely different professional every time technology changes. The goal is to add new capabilities to an existing foundation.

That’s how careers remain resilient.

Adaptation Isn’t Always Optional: Lessons from Tim

Curry’s later career offers a different but equally important lesson.

After suffering a stroke in 2013, Curry’s mobility was significantly affected. Yet he remained connected to his craft through voice work, cameo appearances and other projects. Reuters reports that he returned to the big screen in 2024 in the horror film Stream.

His career didn’t continue exactly as it had before, it evolved. The distinction matters.

We sometimes talk about career reinvention as if it is a grand strategic choice.

Sometimes it is, but sometimes circumstances force it.

Technology professionals know this feeling well:

• A programming language loses popularity.
• A platform gets retired.
• A company changes direction.
• A product disappears.
• A skill that was highly valued five years ago becomes less important.

The response cannot always be ‘wait for the industry to come back.’

It’s often an indicator that it is time to learn something adjacent.

The good news is that technology experience is incredibly transferable.

Your Legacy Should Be More Than Code

There is another important lesson here for senior and mid career technology professionals.

Your legacy should not simply be the software you built.

It should also be the people you helped build:

• Did you document the system?
• Did you mentor someone?
• Did you explain why something worked the way it did?
• Did you make it easier for the next developer to maintain your code?
• Did you challenge the organization when a better solution was available?
• Did you help someone younger become confident enough to take over?

These activities may not appear on a project status report, but, ultimately, they may be some of the most valuable things you accomplish.

Parton’s philanthropic legacy provides an excellent illustration of this principle. Her Imagination Library, launched in 1995, has distributed more than 304 million free books to children around the world. You read that right, 304 million free books. Curry, also a voracious reader created the Tim Curry Endowment for Youth Writing Programs Fund, which helps foster the growth and development of young writers,

Regardless of the industry you are in there is something powerful about building something that continues to create value after the original creator has stepped away.

Technology professionals can do this, too.

Third-Party Software Development Can Help Bridge the Gap

Organizations facing a technology succession problem do not necessarily have to choose between hiring a replacement immediately or hedging bets on nothing breaking.

Experienced software development partners can provide additional capacity while knowledge is being transferred.

Services often include:

• Legacy application assessment
• Software modernization planning
• Software audits
• Technical documentation
• Architecture reviews
• Knowledge transfer
• Application maintenance
• Staff augmentation
• QA and testing
• Middleware and integration development
• Custom software development
• On-call technical support

The goal isn’t to replace internal expertise, it’s to protect and extend it.

A third-party team can work alongside senior employees while they transfer institutional knowledge to the next generation. The right partner can also provide additional technical capacity if internal teams are stretched too thin to modernize systems while keeping the business running.

This approach can be particularly useful when an organization has a retiring senior technology resource who holds years of undocumented institutional knowledge.

A structured transition can capture that knowledge while there is still time.

This might include documenting architecture, identifying critical dependencies, reviewing source code, mapping integrations, creating runbooks and pairing experienced specialists with the people who will eventually take over.

I think we can all agree, it is much easier to transfer knowledge when the expert is sitting beside you than when their name has already disappeared from the company directory.

The Technology Industry Doesn’t Need More People Who Know Everything

It needs more people who are willing to keep learning.

Nobody can know everything anymore; technology is changing too quickly for this to even be reasonable.

The most successful technology professional of the future isn’t necessarily the person who can memorize the most frameworks.

It is the person who knows how to:

• Learn.
• Investigate.
• Ask better questions.
• Understand the business problem.
• Collaborate with specialists.
• Adapt when the first solution doesn’t work.
• And how to take decades of experience and apply it to a completely different technological environment.

Experience only remains valuable when it continues to evolve.

Be a Good Human and Leave Something Behind

The deaths of Dolly Parton and Tim Curry are reminders that careers eventually become legacies.

For the tech industry, their passing should prompt some uncomfortable but useful questions:

• What happens to systems someone understands when they leave?
• Who knows what that someone knows?
• Is existing documentation good enough for someone else to take over?
• Has the knowledge that exists in only their head been shared with anyone?
• Are the mid career team members still learning?
• Is mentoring part of the fabric of your team?

And perhaps the most important question for your team and your company:

What do you want to be remembered for?

Maybe it’s a brilliant application.

Maybe it’s an architecture that lasted 20 years.

Maybe it’s a modernization project that saved a company millions.

Maybe it’s the technical standard you established.

Or maybe it’s the five developers you mentored who went on to build things you never imagined.

The beauty of a career in technology is that you don’t have to remain the same person you were when you started. You can keep adapting, keep learning, keep contributing, keep reinventing, and eventually, leave the technology, knowledge and people around you a little better than you found them.

The goal of a long career isn’t to remain unchanged while the world changes around you , the goal is to keep changing in ways that make your experience more valuable, not less.

And perhaps it’s the real wake-up call for the tech industry.

The post Tech Needs More Tims and Dollys first appeared on STEP Software.

And then… the people who were supposed to use it don’t.

The feature sits there quietly, gathering digital dust, much like that New Year’s resolution purchase of a treadmill.

This problem is becoming increasingly visible with rapid adoption of AI.

Businesses are spending heavily on artificial intelligence and embedding AI capabilities into existing applications, but access and adoption are not the same thing. On a recent episode of AI Decoded, BBC examined this issue describing it as an ‘adoption gap’ between employees having access to AI tools and using them meaningfully. The program also highlighted a gap between AI training and access to AI tools.

CIO.com is seeing a similar shift at the enterprise level. Its 2026 State of the CIO research found that only 19% of respondents said their AI initiatives had met or exceeded business goals, while 18% said fewer than one-third of their AI use cases were meeting defined expectations. CIO identified unclear ROI metrics, unclear corporate strategy, and lack of in-house expertise among the barriers to scaling AI successfully.

The message for business leaders is straightforward:

The problem may not be that your users don’t want AI. The problem may be that you built an AI feature they don’t need.

The Technology is Not the Product

This is one of the most important distinctions in modern software development.

AI is a technology, and not automatically a product strategy.

Consider a hypothetical customer service application:

A stakeholder might decide that the application needs an AI-powered conversation summarizer because competitors have one.

The development team builds it. The model produces beautifully formatted summaries.

Everyone is impressed … except the customer service representatives.

Why?

Because their actual problem isn’t summarizing conversations. Their problem is finding the customer’s previous commitments, identifying unresolved issues, and understanding what needs to happen next.

The AI summary may be technically excellent and operationally useless.

That is a product-design failure, not a model failure.

Stakeholders Know the Business. Users Know the Work.

This distinction is crucial.

Executives understand strategic priorities, product leaders understand market requirements, IT leaders understand architecture, security and operational constraints, developers understand how to build the solution. But end users understand the thing none of those groups can replicate, what it is actually like to do the job.

Only end users know:

• Which screen(s) they leave open all day.
• Which spreadsheet exists because the official application doesn’t quite do what they need.
• Which reports they export and manipulate manually.
• Which field they enter incorrectly (repeatedly) because the interface makes it confusing.
• Where the five-minute task becomes a 45-minute task, every single time.

This information is gold during software discovery and is often missing from the requirements document.

The AI Adoption Gap Is Really a Workflow Gap

Reuters reported in August that established technology companies are emerging as unexpected beneficiaries of the AI boom because businesses are moving from experimentation toward deployment. But the article also highlights the difficulty of integrating AI with existing software, data and operational processes.

This is an important distinction.

Adding AI to an existing application does not automatically redesign the process surrounding that application.

If an employee previously had to complete five screens, obtain two approvals, and send an email before completing a task, adding a chatbot to the first screen doesn’t necessarily fix anything.

That new chatbot may have simply been added to a bad workflow.

A better question to ask is:

“If we could redesign this process from scratch, what would we actually want the user to do?”

Once you have these answers, only then should you ask where AI can help.

More AI Does Not Automatically Mean More Productivity

There is also growing evidence that AI adoption should not be measured simply by usage.

CIO.com reported in June that organizations are increasingly moving away from measuring success through adoption alone and toward measurable business value. Some organizations have burned through AI budgets while encouraging employees to experiment broadly, prompting IT leaders to focus more heavily on high-impact use cases and cost controls.

Ars Technica recently reported on analysis of 15 million real AI interactions that found most tasks at most jobs were unaffected by AI.

That doesn’t mean AI isn’t useful; it means something more nuanced: AI is useful where it fits the work.

A feature that saves a user 30 seconds once a month is technically automation and likely not a good strategic investment. A feature that eliminates 30 minutes of repetitive work every day for 500 employees is a vastly different conversation.

This is why use-case selection matters.

Build What Is Needed, Not What Sounds Impressive

The correct solution begins with better discovery.

Before approving another AI feature, organizations should ask: “What problem are we trying to solve?”

If the answer is ‘we need an AI feature,’ stop, immediately.

That’s a technology requirement, not a business problem.

Instead ask:

• What task is taking too long?
• What information is difficult to find?
• Where are employees repeatedly entering the same information?
• Where are errors occurring?
• What decisions are being delayed?
• What work is repetitive but still requires human review?
• What part of the workflow creates the most frustration?

Then quantify the problem:

• How many users experience it?
• How frequently?
• How much time does it consume?
• What does that time cost?
• What happens when something goes wrong?

Once you have these answers you will have something worth designing around.

Prototype Before You Build the Ferrari

An often overlooked and useful change is moving more of the investment upstream. Instead of spending months building the complete AI capability, create a prototype.

Put the prototype in front of real users, watch them use it and equally important, watch what they don’t use. That last part can be uncomfortable; users may ignore the feature you spent the most time building.

Good.

You just learned something before spending even more money.

Software development should not be a contest to see who can turn a requirements document into production code the fastest. Instead, it should be a process of reducing uncertainty.

Where a Third-Party Software Developer Can Help

This is where an experienced external software development partner can provide considerable value.

A third-party team can sit between business stakeholders, IT and end users and ask some uncomfortable but useful questions.

• Is this actually the problem?
• Does AI solve it?
• Could an existing application be modernized instead?
• Would an API or middleware layer solve the integration problem?
• Could workflow automation deliver the same result at a fraction of the cost?
• Does solving this problem add or subtract from existing technical debt?
• What happens if we don’t build this?

Those questions can save money; they can also save development capacity. But more importantly, they can prevent a common enterprise technology problem: continuing to spend money on a solution simply because the organization has already spent money on it.

That is the sunk-cost trap.

If users aren’t adopting a feature, the answer isn’t necessarily another round of training.

Sometimes it is better discovery, sometimes it is redesign, sometimes it is fixing the workflow underneath the feature. And sometimes, it’s admitting that the original idea was wrong; that’s not failure, that’s good software engineering.

The Best AI Feature Might Be the One You Don’t Build

There is tremendous pressure on organizations to demonstrate that they are doing something with AI. This pressure can produce some impressive demos; it can also produce software nobody uses and balloon AI technical debt.

The organizations that get the most value from AI will likely be the ones that become disciplined about distinguishing technology possibility from business value.

CIO.com’s 2026 research makes that shift particularly clear: organizations are moving toward structured governance, measurable KPIs and use-case prioritization rather than simply launching more pilots.

The same principle applies whether the feature uses AI, automation, APIs, cloud computing or something that has been sitting in the technology toolbox for twenty years.

• Start with the user.
• Understand the problem.
• Redesign the workflow.
• Choose the technology.
• Build the smallest useful solution.
• Measure the result.
• Scale what works.

Because ultimately, your software doesn’t get a return on investment because it is clever, it gets a return because someone uses it to accomplish something that matters. If your latest AI feature isn’t getting used, don’t immediately blame your users; they may be telling you something much more valuable:

You built the wrong thing.

And that’s a problem worth solving and where a trusted software development partner can help you get there.

We’ve been helping businesses solve their most annoying software challenges for over 20 years, reach out to our advisors for a complimentary 30-minute call before that next feature joins a growing collection of very impressive software nobody opens.

The post AI: We Have a Problem! first appeared on STEP Software.

At STEP Software, we’ve written about everything from AI technical debt and data quality to edge computing, embedded systems, cybersecurity, digital sovereignty and software architecture.

On the surface, those topics might look like an eclectic collection.

Look a little closer, though, and three common threads emerge that tell us quite a bit about where software development and business technology are heading.

1. Software Modernization Is Becoming More Important Than Replacement

One of the strongest themes running through our 2026 articles is the realization that software modernization does not automatically mean replacing existing software.

This distinction matters.

Businesses have spent decades building critical software applications around the way they actually operate day to day. Those applications may not be pretty. They may use older programming languages, databases or architectures that would make a modern developer cringe with fear.

But what they often contain, which is even more valuable is business knowledge.

This is why legacy software modernization continues to be such an important conversation for business and technical leaders.

Legacy applications often contain years of business logic, workflows, integrations and institutional knowledge. Replacing them can introduce significant cost and risk, particularly when the existing system remains stable and mission critical.

Modernization does not have to mean starting from scratch. In fact, Google Cloud’s guidance on legacy modernization similarly emphasizes that modernization can involve everything from rehosting and re-platforming to refactoring and replacing individual components.

Sometimes the right answer is a complete replacement. Often, it isn’t.

A legacy application might benefit from a modern user interface. A database might need optimization. Two disconnected systems might need middleware or API integration. A manual workflow might be a candidate for automation. An application might benefit from moving certain workloads to the cloud while keeping other components where they are.

Modernization can be surgical. And in an environment where IT budgets are being scrutinized, that can be a very good thing.

The question isn’t necessarily:

“What should we replace?”

It may be:

“What can we improve without throwing away what already works?”

2. Technical Debt Has Become a Business Problem

The second most common thread is considerably less glamorous, but potentially much more expensive.

Technical debt.

In June, we wrote about being Buried in Technical Debt, following our earlier discussion of AI Technical Debt both of which were predated by The True Cost of Technical Debt from July 2025.

We also explored data quality, credential sprawl and cybersecurity.

These subjects have something important in common: problems that are easy to postpone can quietly become considerably harder and more expensive to solve later.

Technical debt isn’t necessarily the result of bad decisions.

Sometimes it is the result of perfectly reasonable decisions made under pressure.

A company needs a new feature, so the team takes the fastest route.

A system needs to stay online, so the upgrade gets postponed.

A developer leaves, and documentation gets pushed down the priority list.

An integration is held together with a script that everyone knows nobody should touch.

Then another year passes. And another.

And before you know it, the organization isn’t simply maintaining software: it’s maintaining the history of every shortcut it ever took.

The same principle applies to data.

STEP’s Garbage In, Garbage Out: The 2026 Edition explores why data quality has become a business-critical issue. Poor data can undermine software projects, increase operational costs, create security risks and make analytics and automation considerably less effective.

Cybersecurity belongs in this conversation, too.

Our recent article on credential sprawl looks at how unmanaged accounts and access credentials can create costs and security risks that quietly accumulate over time.

Technical debt, poor data and credential sprawl may sound like separate IT problems.

They aren’t.

They are all examples of technology complexity creating a business cost.

This is why technical debt deserves a seat at the business table.

It affects budgets.

It affects productivity.

It affects cybersecurity.

It affects employee experience.

And eventually, it affects how quickly a business can respond when an opportunity appears.

Ignoring technical debt doesn’t make it disappear.

It simply lets the interest accumulate.

3. The Human Side of Technology Matters More Than Ever

The third thread we’ve talked a lot about, is from our perspective, the most important one.

Technology is still about people.

This may sound obvious, but it is remarkably easy to forget when the conversation is dominated by automation, AI, cloud platforms and increasingly sophisticated software.

STEP’s recent conversations around technology and people have reinforced an important point: organizations need to think beyond technology adoption and consider the people expected to build, manage and use that technology.

This matters because technology initiatives don’t happen in a vacuum.

Someone must:

• Implement them
• Maintain them
• Explain them to the business
• Train employees to use them
• Ultimately, make the decisions when the technology should not be used

And someone inevitably must answer the question:

“Why does this button work differently now?”

Technology can improve a business dramatically, but only when people can work effectively alongside it.

This means investing in skills, documentation, communication, usability and good software architecture.

It also means recognizing that developers, IT teams and technical specialists are not infinite resources.

Burnout should not be a capacity-planning strategy.

So, What Does This Mean for the Rest of 2026?

If the first two thirds of the year are any indication, successful IT strategies will be less about doing everything and more about doing the right things, deliberately.

Modernize where and when modernization creates value.

Address technical debt before it becomes an emergency.

Improve data before building another system on top of bad data.

Strengthen cybersecurity and resilience, constantly.

Invest in people as seriously as you invest in technology.

And perhaps most importantly, don’t assume that every technology problem requires a technology replacement.

Sometimes, the smartest investment is the one that makes the technology you already own work considerably better.

And this is where custom software development can become a strategic business tool rather than simply another line item on the IT budget.

A custom software development partner can help organizations assess existing systems, identify modernization opportunities, build integrations, improve applications and create a practical roadmap for technology investment.

STEP Software has spent more than two decades working across the full spectrum of software engineering and custom software development, including legacy systems, modernization and complex business applications.

Because sometimes the smartest technology strategy isn’t buying something new.

It is making what you already have work better.

That has been one of the biggest themes running through STEP Software’s 2026 conversations so far.

Technology doesn’t have to be shiny to be strategic.

Sometimes it just needs to work. Drop us a line if it’s time to review your software landscape and a strategic, budget friendly path forward.

The post The Top 3 Software Trends We’ve Seen in 2026, So Far first appeared on STEP Software.

Open almost any technology publication, news feed or social media platform and you will find AI. AI in your browser. AI in your database. AI in your image searches. AI in your coffee maker. Chances are, it’s AI writing those articles about AI.

But underneath all the AI noise, something rather encouraging is happening.

Software itself continues to get better.

Open-source projects are becoming more secure. Programming languages are getting safer. Databases are becoming more capable. Cloud infrastructure is becoming easier to manage. And developers are finding new ways to build software that is faster, more resilient and more respectful of privacy.

This is good news for business leaders because these advancements do not require organizations to full rip and replace of everything it already owns.

In fact, it’s quite the opposite.

The real opportunity is often figuring out how to take these advancements and apply them to the systems, applications and processes already running the business.

So we don’t contribute to more AI Brain Fry, we thought our readers would appreciate hearing about some recent newsworthy software advancements that are getting our brains fired up right now.

1. PostgreSQL Continues to Get Better, Not Just Bigger

PostgreSQL may not generate the same headlines as the latest consumer technology launch, but it quietly remains one of the most important pieces of software in the modern technology ecosystem.

In July, the PostgreSQL Global Development Group released the second beta of PostgreSQL 19, moving the open-source database another step toward its planned September 2026 production release. PostgreSQL also released security and maintenance updates across supported versions in May, addressing 11 security vulnerabilities and more than 60 bugs.

Why is this a feel-good story?Because it demonstrates something business leaders often forget; software does not have to be replaced to be modern. It can evolve.

PostgreSQL has been under active development for more than 35 years, and organizations continue to benefit from that ongoing investment.

This opens an interesting modernization conversation for businesses.

Instead of replacing an entire application, could the database be modernized? Could performance be improved? Could older integrations be replaced with APIs? Could the application interface be refreshed while preserving the business logic that has worked for years?

Sometimes modernization is less ‘rip it out’ philosophy and more of a ‘make what we have considerably better’ philosophy.

This is often a much easier conversation to have with the CFO.

2. Rust Keeps Making Software Safety More Practical

Another quiet software success story is Rust, the programming language increasingly used for applications where performance and memory safety matter.

Rust released version 1.97.1 on July 16, fixing an LLVM-related mis-compilation issue, following the major 1.97.0 release just a week earlier. The project has maintained its regular release cadence throughout 2026.

The interesting part isn’t simply another version number.

Rust represents a broader movement in software development toward building safety into the language itself rather than relying entirely on developers and testing to catch certain classes of problems.

This matters when organizations are modernizing legacy systems.

Businesses with applications-built decades ago may not need to rewrite everything in Rust. But newer components, security-sensitive services and performance-critical applications may provide opportunities to introduce safer technologies incrementally by applying a Strangler Fig methodology.

This is an important distinction it means modernization does not have to mean a five-year rewrite. Instead, it can mean strategically replacing the pieces that present the greatest risk or create the greatest operational drag.

3. Cloud Security Is Becoming Easier to Automate

In June, AWS announced a new Workload Credentials Provider designed to automate the delivery and renewal of certificates and secrets for applications. The open-source tool is intended to reduce custom automation and help prevent outages caused by expired credentials, while working across AWS and non-AWS environments.

This may not sound particularly glamorous.

There are no robots. No holograms. No dramatic keynote.

But anyone who has dealt with an expired certificate at 2:00 a.m. knows that boring software improvements can be spectacularly useful.

Automating certificate and credential management reduces repetitive work, removes opportunities for human error and can make infrastructure more resilient. And this is where software development becomes a business conversation.

Many organizations have accumulated years of scripts, workarounds and manual processes around their infrastructure.

If a process is important enough to require a spreadsheet, three passwords and ‘Bob from IT’ remembering what happened last time, there may be an opportunity for software to improve it.

4. Cloudflare Opens Up a Privacy Tool

In July, Cloudflare open-sourced a debugger designed to help developers work with privacy-preserving protocols used by major technology companies including Apple and Microsoft. The project is aimed at making complex privacy technologies easier for developers to inspect and troubleshoot.

This is a particularly encouraging development because privacy-enhancing technology has historically been difficult to understand and even harder to implement correctly.

Open-source tooling can change that equation.

When developers can inspect, test and improve tools collaboratively, useful technology can spread faster and become less dependent on a handful of vendors.

For business leaders, the larger lesson is about technology choice.

Open source is not simply about saving money; it can provide flexibility, transparency and access to a much larger development community.

Of course, open source still needs governance, security reviews and responsible maintenance. But organizations that completely ignore it may be limiting their technology options unnecessarily.

5. The Internet Is Experimenting with a More Open Social Model

One of the more interesting developments outside traditional enterprise software is the continued evolution of Bluesky and the AT Protocol.

Bluesky’s new CEO, Toni Schneider, recently described a vision for an open social ecosystem in which users can move between interoperable applications while maintaining greater control over their identity and data. The ecosystem already includes more than 1,000 interoperable applications.

Whether Bluesky ultimately becomes a mainstream competitor to today’s dominant social platforms is almost beside the point. The encouraging software idea here is interoperability. Instead of one company owning the entire experience, different applications can participate in a shared protocol.

That is hardly a new concept. Email works this way. The web works this way. APIs work this way. And it is a useful reminder for business leaders that technology does not always need to be built as a giant monolithic platform.

Well-designed systems can communicate, they can exchange information, they can evolve independently, and they can be replaced piece by piece rather than all at once.

The Best Software News May Be the Quiet Stuff

None of these stories involves a magical button that transforms an entire business overnight, and that is precisely why they are worth paying attention to.

The most valuable software advancements are often incremental:

• A database becomes more secure.
• A programming language prevents an entire class of bugs.
• A tedious infrastructure task becomes automated.
• A complicated privacy technology becomes easier to work with.
• An application ecosystem becomes more open and interoperable.

Those improvements compound.

For business leaders, this creates an important opportunity. You do not necessarily need a giant technology transformation to make a meaningful difference to the business.

Sometimes you need to modernize one application.

Sometimes you need middleware to connect two systems that were never designed to talk to each other.

Sometimes an aging database needs attention rather than replacement.

Sometimes a manual process deserves automation.

And sometimes the best technology strategy is simply having someone experienced enough do an audit of the entire environment and identify where a relatively small software investment could remove a surprisingly large business headache.

Technology keeps moving forward.

The trick for business leaders is not trying to chase every advancement.

It is knowing which ones are worth bringing home and when to reach out for help charting the course.

The post Second Page News: August Edition first appeared on STEP Software.

It is not a medical diagnosis, or a term found in a psychology textbook (yet). Instead, it is the growing feeling of mental fatigue, cognitive overload, and reduced critical thinking that can occur when employees rely heavily on generative AI throughout the workday.

For business leaders, this is more than a cheeky workplace term; it’s becoming a business issue that affects productivity, innovation, employee development, risk management, and budgets.

The irony is hard to miss. The very tools designed to make us work smarter can, if used without balance, make us think less.

What Is AI Brain Fry?

AI Brain Fry has been described as the mental exhaustion and reduced cognitive engagement that some workers experience after spending extended periods interacting with AI tools. Instead of analysing problems, brainstorming solutions, or writing from scratch, employees increasingly prompt AI systems, review responses, make edits, and repeat the process dozens or even hundreds of times each day.

The work may feel easier, but it often requires a different type of concentration.

Microsoft’s 2025 Work Trend Index found that employees are experiencing an ‘infinite workday’ as AI accelerates expectations for productivity, increasing the volume of information and decisions workers process rather than reducing them.

Research from Harvard Business School also suggests that while generative AI can significantly improve productivity for many knowledge tasks, over-reliance may reduce opportunities for learning, experimentation, and independent problem solving, particularly among less experienced employees.

In other words, AI can make people faster, but it does not automatically make them better thinkers.

Why This Is Becoming a Business Problem

Most discussions about AI focus on technology implementation, and how to get it into the budget.

The bigger challenge, however, may be the impacts on human performance.

Employees who spend their day evaluating AI-generated content often report:

• Decision fatigue
• Difficulty concentrating
• Reduced confidence in their own judgement
• Less creative thinking
• Increased mental exhaustion

The World Economic Forum’s Future of Jobs Report 2025 warned that AI adoption will require organisations to invest heavily in human skills such as analytical thinking, creativity, resilience, and lifelong learning because these abilities will become more valuable, not less, as automation increases. We touched on this recently in our blog Humans in an AI Time.

So, what does this mean for businesses?

The effects are company wide:

• Marketing teams reviewing dozens of AI-generated campaigns may struggle creatively
• Developers validating AI-written code may lose confidence
• Legal teams checking AI-assisted contracts may face decision fatigue
• Finance professionals reviewing AI-produced analyses may question their judgement
• Customer service representatives refining AI-generated responses may become mentally exhausted
• Everyone still needs to think critically, but HR gets to deal with the back lash from all the departments

The Hidden Cost of Convenience

One of AI’s greatest strengths is reducing repetitive work. One of its greatest risks is reducing ‘productive struggle.’

Stanford professor Jo Boaler sings the praises of ‘embracing the struggle’ when it comes to learning, psychologists concur on the value of doing things the hard way.

Consider a junior software developer.

Ten years ago, they might spend several hours researching documentation, testing different approaches, making mistakes, and eventually solving a problem.

Today, AI may generate a working solution in seconds.

This sounds like progress, and often it is.

But, if developers never learn why the solution works, organisations risk creating teams that can implement code but struggle to troubleshoot, optimise, or innovate when AI cannot provide the answer. We touched on this back in February in our blog: AI Coding Agents: Yes, Maybe, or No?

These same principles apply across accounting, engineering, marketing, human resources, and operations departments.

Efficiency without understanding creates organisational risk

Why Budgets Should Be Part of the Conversation

At first glance, AI Brain Fry appears to be a people issue, but the financial implications are real.

Consider this:

• If employees require more time to verify AI output, productivity gains shrink
• If poor AI decisions create compliance issues, costs increase
• If employees experience higher levels of mental fatigue, absenteeism and turnover can rise

Gallup estimates that employee disengagement costs the global economy trillions of dollars annually through lost productivity. While AI is not the sole cause of disengagement, organisations should ensure technology improves work rather than simply increases the pace.

Businesses investing heavily in AI must invest equally in developing critical thinking, governance, training and AI literacy.

AI Needs Adults in the Room

Generative AI works best when paired with experienced professionals. It is an assistant not an autopilot.

Successful organisations are establishing practical guidelines encouraging employees to:

• Verify AI-generated information
• Understand outputs before using them
• Continue developing technical and professional expertise
• Use AI to accelerate work, not replace judgement
• Take regular screen breaks to reduce cognitive fatigue

Think of AI like GPS, it is incredibly useful, but, if you follow every instruction without paying attention to the road, eventually you are going to end up somewhere unexpected.

Building a Healthier AI Workplace

Business leaders can reduce AI Brain Fry by creating a balanced approach to AI adoption.

Some practical strategies include:

Invest in AI literacy. Employees should understand both the strengths and limitations of generative AI.

Encourage independent thinking. Not every task needs an AI prompt. Brainstorming, strategic planning, and problem solving still benefit from human collaboration.

Protect deep work. Constant prompting and reviewing AI outputs fragments attention. Dedicated time for uninterrupted work improves focus and creativity.

Review workloads. AI often increases expectations rather than reducing them. Ensure productivity targets remain realistic.

Support continuous learning. Employees should continue developing their technical expertise instead of relying solely on AI-generated answers.

How STEP Software Can Help

Many organisations are discovering that successful AI adoption is less about the technology itself and more about implementation.

Introducing AI without governance, training, or process improvements can create confusion instead of efficiency.

At STEP Software, we help organisations modernise technology while keeping people at the centre of the solution.

Whether developing AI-ready applications, integrating new technologies into existing systems, modernising legacy platforms, or providing experienced software professionals through staff augmentation, our focus is on helping businesses use technology strategically.

Sometimes the best way to improve productivity is not by asking your existing team to do more; its by bringing in experienced specialists who can accelerate projects, mentor internal teams, and provide the expertise needed to implement technology effectively.

Final Thoughts

AI Brain Fry may sound like a trendy phrase, but the challenge behind it is real.

As organisations embrace AI across every department, success will depend on maintaining the balance between automation and human expertise.

Technology should reduce repetitive work; it should not reduce critical thinking.

Businesses that invest in both AI and their people will be better positioned than those relying on technology alone.

After all, artificial intelligence may be getting smarter every month; but the real competitive advantage belongs to organisations filled with people who know when not to ask the robot.

Our advisors are here to help, drop us a line if you are feeling the AI Brain Fry in real-time.

The post This is Your Brain on AI: The Hidden Productivity Problem of Brain Fry first appeared on STEP Software.

Fast forward to 2026 and they have become one of the biggest infrastructure stories in technology.

Driven by the rapid growth of AI, cloud computing, digital transformation, cybersecurity requirements, and high-performance computing, organizations around the world are investing billions in new data center capacity. According to Synergy Research Group, global spending on cloud infrastructure services continues to grow by more than 20% year-over-year, while hyperscale providers continue to expand their global data center footprint.

While this expansion creates enormous opportunities for innovation, it also has significant implications for business budgets, IT strategy, and long-term planning.

For business leaders, the data center boom isn’t just an industry headline, it’s something that will influence technology costs for years to come.

Why Are So Many Data Centers Being Built?

The answer isn’t just artificial intelligence.

Although AI workloads require significant computing power, they’re only one piece of a much larger trend.

Organizations are consuming more digital services than ever before:

• Cloud-hosted business applications
• Hybrid work environments
• Data analytics platforms
• Cybersecurity monitoring
• Video collaboration
• Software-as-a-Service (SaaS)
• Internet of Things (IoT)
• Digital customer experiences

Every one of these services relies on computing infrastructure somewhere.

According to Gartner, worldwide spending on public cloud services continues to accelerate as organizations modernize applications and shift away from on-premises infrastructure.

More Users + More Applications + More Data + More Infrastructure = Unprecedented Demand for New Data Centers

Infrastructure Demand Is Changing Technology Economics

Building a modern hyperscale data center isn’t inexpensive.

Facilities require:

• Massive electrical capacity
• Redundant networking
• Specialized cooling systems
• Physical security
• Backup power generation
• Skilled technical staff

According to the International Energy Agency (IEA), electricity demand from data centers is growing rapidly worldwide, making power availability one of the primary constraints.

This increased demand affects everyone.

Whether your business owns servers or consumes cloud services, infrastructure costs eventually flow through to customers.

What This Means for Budgets

It’s a nuanced reality, moving to the cloud doesn’t necessarily automatically reduce IT spending. As infrastructure providers invest billions in new facilities, organizations should expect ongoing pressure in several areas.

1. Cloud Costs Will Continue to Evolve

Cloud providers continually invest in infrastructure, networking, and security. While competition helps stabilize pricing, businesses should anticipate periodic adjustments as providers expand capacity and introduce premium services.

This makes cloud cost optimization more important than ever.

Organizations should regularly evaluate:

• Idle resources
• Storage utilization
• Licensing
• Reserved capacity
• Data transfer costs

Every dollar saved through optimization is one that doesn’t need to be added to next year’s budget.

2. Electricity is Becoming an IT Budget Conversation

Historically, electricity wasn’t something most CIOs discussed during strategic planning.

This is changing.

With data centers being among the largest consumers of electricity globally, utilities in many regions are investing heavily in grid expansion to support future demand. Businesses operating private infrastructure should expect energy efficiency to become a growing operational consideration.

Even organizations that rely entirely on cloud services can anticipate eventually seeing energy-related costs reflected in service pricing.

3. Hardware Planning Requires Longer-Term Thinking

The demand for servers, networking equipment, storage systems, and supporting infrastructure continues to grow. Although supply chains have improved since the pandemic, enterprise hardware procurement still requires careful planning as highlighted by the 2026 RAM crisis.

Organizations delaying infrastructure refreshes may find themselves competing for limited availability during periods of high demand or facing increased costs associated with ongoing supply imbalances.

Strategic planning is becoming equally as important as purchasing.

Why Business Leaders Should Pay Attention

It’s easy to assume this is an issue only for IT departments.

It isn’t, this is a business problem.

Technology infrastructure supports every business function:

• Sales
• Finance
• Operations
• Manufacturing
• Customer service
• Human resources

When infrastructure costs change, every department feels the impact, eventually.

Forward-thinking organizations are already asking:

• How can we optimize cloud spending?
• Which legacy applications should remain on-premises vs. a hybrid approach?
• Which systems should be modernized?
• Can middleware extend existing platforms instead of replacing them?
• Are we paying for infrastructure we’re no longer using?

These aren’t just technical questions; they’re financial ones.

The Hidden Opportunity

The data center boom isn’t simply about higher costs., it’s also an opportunity to become more efficient.

Organizations that modernize legacy applications, improve software architecture, eliminate technical debt, and optimize cloud environments often reduce infrastructure requirements while improving performance. Modern software typically consumes fewer resources, scales more efficiently, and costs less to maintain than aging applications designed for a different era.

These are just a few of the reasons application modernization has become a boardroom discussion rather than just an IT initiative.

How STEP Software Can Help

Infrastructure investments are only one side of the equation.

Making better use of existing technology is often the fastest and most cost-effective strategy.

At STEP Software, we help organizations maximize the value of their technology investments through:

• Legacy application modernization
• Middleware integration
• Custom software development
• Software and technical audits
• Software performance optimization
• Cloud-Hybrid architecture optimization
• Technical documentation
• Staff augmentation

Rather than replacing systems prematurely, many organizations can extend the life of existing applications while improving performance and reducing operational costs. Strategic management of infrastructure creates flexibility for future planning while protecting previous technology investments.

Looking Ahead

The global data center expansion isn’t slowing down. As businesses continue generating more data and adopting more digital services, infrastructure demand will only increase.

For business leaders, the question isn’t whether the technology landscape is changing. It’s whether your organization is prepared to adapt.

Organizations that actively monitor infrastructure trends, optimize technology spending, modernize strategically, and build flexible IT roadmaps will be far better positioned than those reacting after budgets begin to tighten.

The data center boom isn’t just reshaping the technology industry; it’s reshaping how businesses plan, invest, and compete.

Drop us a line if you are looking for help uncovering optimization opportunities in your organization.

The post The Cost of Doing Data: What the Data Center Boom Means for IT Budgets first appeared on STEP Software.

For IT leaders, these events highlight an important question:

If your team couldn’t access the office tomorrow, could your business continue operating?

Disaster Recovery Plans (DRPs) and Business Contingency Plans (BCPs) are often written to satisfy compliance requirements or insurance audits. Unfortunately, many organizations don’t revisit them until an actual emergency exposes the gaps. The reality is today’s business environment changes far more quickly than annual documentation updates can keep pace with.

The widespread Canadian wildfires are a timely reminder that every organization should review, test, and update its disaster recovery strategy at least once every year.

Disaster Recovery Isn’t Just About Technology

When many organizations think about disaster recovery, they immediately focus on backups, cloud infrastructure, and server redundancy.

Those are certainly critical components, but they’re only part of the picture.

A comprehensive Disaster Recovery Plan should answer questions such as:

• What happens if your office becomes inaccessible?
• Can employees securely work remotely?
• What if key members of your IT team are personally affected by the disaster?
• Are critical vendors able to continue supporting your systems?
• How quickly can business-critical applications, including legacy systems, be restored?
• Who has decision-making authority if leadership is unavailable?

Natural disasters rarely affect only one component of an organization. They impact people, communications, transportation, utilities, supply chains, and customer expectations simultaneously.

The Government of Canada’s Public Safety Department recommends that business continuity planning address ‘all hazards,’ including natural disasters, utility outages, pandemics, and cyber incidents because these events can have cascading operational impacts.

Annual Reviews Matter More Than Ever

Technology changes rapidly. Your Disaster Recovery Plan should evolve just as quickly.

Over the course of a year your organization may have:

• Migrated systems to the cloud
• Implemented new SaaS platforms
• Changed cybersecurity tools
• Replaced networking infrastructure
• Overhauled a legacy system
• Implemented AI tools
• Added new remote workers or new technical staff
• Lost institutional knowledge through employee turnover

If your DRP still references retired servers, former employees, or outdated vendor contacts, it can’t be relied on during an emergency.

The National Institute of Standards and Technology (NIST) recommends organizations maintain, review, and regularly test contingency plans whenever significant technology or organizational changes occur.

Similarly, ISO 22301, the international standard for Business Continuity Management Systems, requires organizations to regularly exercise, evaluate, and continually improve their business continuity plans to ensure they remain effective as business conditions evolve.

A plan that has never been tested is just a theory.

The Human Side of Disaster Recovery

Natural disasters, like wildfires should remind us that technology doesn’t work without people.

The impact is real:

• Employees may be displaced from their homes.
• Internet connectivity may become unreliable.
• Schools may close unexpectedly.
• Staff may need time away to care for family members or evacuate affected areas.

Building resilience means recognizing that your people are your most valuable resource.

Research from Deloitte’s Global Resilience Report consistently shows that organizations with mature resilience programs place equal emphasis on people, operational processes, technology, and external partnerships when preparing for disruptions.

Cross-training staff, documenting critical systems, and ensuring multiple people understand key applications reduces reliance on individual employees during emergencies.

Good documentation becomes invaluable when your subject matter expert is displaced or simply isn’t available.

Third-Party Partners Should Be Part of Every DRP

One area that organizations frequently overlook is the role of trusted external partners.

Even the best internal IT teams have limits.

If multiple team members are unavailable during an emergency, projects don’t stop, production systems still require support, and customers continue expecting service.

This is where strategic third-party partners become an essential part of business continuity.

According to Gartner, organizations are increasingly adopting ecosystem resilience strategies that include trusted technology partners to improve operational continuity and reduce recovery times during business disruptions.

Rather than scrambling to locate emergency assistance during a crisis, organizations should establish relationships with experienced technology partners before they need them.

Trusted third-party vendors can provide:

• Emergency application support.
• Additional development resources.
• Legacy system expertise.
• Infrastructure troubleshooting.
• Production monitoring.
• Software maintenance.
• Documentation assistance.
• Quality assurance and testing.
• Knowledge transfer for critical systems.

Having these relationships already in place can dramatically reduce recovery time while easing pressure on internal teams. Think of your external technology partner as an extension of your own IT department; not just a vendor you call when things go wrong.

Where STEP Software Fits into Your Recovery Strategy

Business continuity isn’t only about recovering servers; it’s about ensuring your business can continue delivering value to customers.

Here at STEP, we’ve spent more than 20 years helping organizations support, maintain, modernize, and extend business-critical applications.

Whether your environment includes modern cloud platforms, aging legacy systems, custom business applications, or a combination of technologies, having experienced specialists available can significantly reduce operational risk during unexpected disruptions.

Our team can assist organizations by providing:

• Third-party application support.
• Legacy software expertise.
• Software maintenance.
• On-demand development resources.
• Knowledge transfer and technical documentation.
• Quality assurance services.
• Custom software enhancements.
• Long-term modernization planning.

We routinely work alongside internal IT departments, meaning we can integrate into existing teams quickly when additional capacity is needed. This flexibility becomes especially valuable during periods of unexpected disruption.

Don’t Wait for the Next Emergency

The best DRPs are written during calm periods, not during emergencies.

The Canadian wildfires remind us that organizations cannot predict when the next disruption will occur, only that another disruption is inevitable.

Whether the challenge is a natural disaster, cyberattack, prolonged power outage, infrastructure failure, or critical staffing shortage, resilient organizations prepare before they need to respond.

Take the opportunity to review your DRP this year with a special focus on:

• Verifying your contact lists.
• Reviewing vendor agreements.
• Testing your backup and recovery procedures.
• Validating remote work capabilities.
• Updating documentation.
• Identify single points of failure.

Finally, ask one question:

If something happened tomorrow, would your organization have the people, processes, technology, and trusted partners needed to continue serving your customers?

If the answer isn’t a confident ‘yes,’ now is the time to strengthen your plan.

Drop us a line if you need help fortifying your DRP.

The post Canadian Wildfires Are a Wake-Up Call: Why Every IT Leader Should Review Their Disaster Recovery Plan first appeared on STEP Software.

Not because people aren’t working hard enough, quite the opposite, they are masters of juggling full plates with competing priorities.

Many IT professionals, developers, project managers, cybersecurity specialists, and technology leaders are working harder and staying connected longer than ever before. Smartphones, collaboration tools, cloud platforms, and remote work have created a world where it is possible to be available around the clock.

The challenge is that our brains were never designed to operate this way.

As we discussed in our recent STEP Software blogs, Mental Health in IT and Humans in an AI Time, technology may power modern business, but people remain at the center of every successful project. Protecting the wellbeing of those people is not simply a workplace benefit; it’s a business strategy.

Increasingly, the science suggests that taking time off, developing non-technology-based hobbies, and intentionally disconnecting from work can improve performance, creativity, decision-making, and long-term employee retention.

The Science of Stepping Away

Researchers refer to the ability to mentally disconnect from work during personal time as psychological detachment.

A 2025 longitudinal study published in the Journal of Happiness Studies found that psychological detachment from work is a key driver of employee wellbeing across multiple measures, including emotional health, job satisfaction, and overall life satisfaction. The researchers found that the benefits were consistent across employee groups and industries.

This builds on years of previous research. Studies from organizational psychologist Sabine Sonnentag found that employees who successfully disconnect from work during non-working hours experience lower psychological strain, higher life satisfaction, and improved job performance when they return to work.

The key takeaway is surprisingly simple:

Recovery is not the opposite of productivity. Recovery enables productivity.

Why This Matters More in IT

Technology professionals often face unique workplace pressures:

• Tight and often unrealistic project deadlines
• Systems that require constant monitoring
• Unexpected security incidents
• Technical debt accumulation
• New pressures added by AI adoption and integration
• Legacy systems and the drag on innovation

Critical infrastructure cannot simply be turned off at the end of the day.

As a result, many IT professionals develop habits of constant connectivity.

The problem with this is that sustained cognitive effort without recovery eventually reduces performance.

Research has repeatedly shown that employees who fail to detach from work are more likely to experience exhaustion, reduced wellbeing, and lower engagement over time. The WHO has gone so far as to classify burnout as an ‘Occupational Phenomenon’ resulting in reduced professional efficacy.

Ironically, the people who feel most indispensable are often the people who need downtime the most.

Why Non-Technology Hobbies Matter

Many technology professionals naturally gravitate toward technology-focused hobbies. There is nothing wrong with enjoying coding projects, gaming, home labs, or experimenting with new platforms.

However, there is growing evidence that activities unrelated to work provide unique recovery benefits.

A 2025 meta-analysis examining vacation and employee wellbeing found that physical activity, social engagement, and complete psychological detachment from work produced some of the strongest improvements in employee wellbeing.

Engaging alternate parts of the brain while providing a sense of accomplishment separate from workplace performance is essential to disconnection success.

Some of these types of activities include:

• Hiking
• Gardening
• Woodworking
• Photography
• Sports
• Music
• Volunteering
• Art
• Reading (a physical paper book)

Many leaders are surprised to learn that these activities can directly improve workplace outcomes. When people return from meaningful downtime, they often bring renewed focus, creativity, and problem-solving ability with them.

Better Leaders Set Better Examples

One of the more interesting findings from workplace psychology research is that employees often mirror the behavior of their leaders.

Research published by Cambridge University Press found that leaders who successfully detach from work during non-working hours indirectly contribute to improved employee wellbeing and recovery. If leadership sends emails at midnight, takes no vacation, and never disconnects, employees often feel pressure to do the same.

Conversely, leaders who model healthy boundaries help create healthier teams.

This is particularly important in today’s technology environment, where burnout continues to be a major concern. Recent industry surveys indicate that burnout remains widespread across technology professions, with many workers reporting significant levels of stress and exhaustion.

The Business Case for Time Off

For business leaders managing budgets, the argument for employee recovery extends beyond wellbeing.

Burnout contributes to:

• Higher turnover
• Increased absenteeism
• Reduced productivity
• Lower engagement
• Increased hiring costs

Replacing experienced technical employees is expensive. Losing institutional knowledge can delay projects and create additional risks for already stretched teams.

Investing in recovery is often significantly less expensive than replacing burned-out employees.

How Staff Augmentation Supports Healthy Teams

One reason employees struggle to take time off is simple: there is nobody available to cover their responsibilities. This is especially common in smaller IT departments where key individuals become single points of failure.

Strategic staff augmentation can help address this challenge.

By working with trusted technology partners, organizations can:

• Support extended vacations
• Cover parental leave
• Manage medical absences
• Reduce pressure during peak project periods
• Maintain business continuity
• Prevent burnout before it occurs

Rather than viewing external resources solely as a project-based expense, forward-thinking organizations increasingly see staff augmentation as a workforce resilience strategy.

When employees know they can take meaningful time off without creating operational risk, everyone benefits.

Final Thoughts

Technology moves quickly.

People do not.

The most successful organizations understand that sustainable performance requires periods of recovery.

Taking time off is not a sign of reduced commitment. Having hobbies outside of technology is not a distraction from professional growth. Disconnecting from work is not laziness.

It is maintenance.

Just as organizations invest in maintaining infrastructure, software, and security systems, they must also invest in maintaining the people who keep those systems running.

Because at the end of the day, the MVP of any technology organization is not the technology itself; it’s the people behind it.

Drop us a line if you are looking for creative ways to augment your team.

The post Powering Off: Why Time Away from Tech Improves Performance first appeared on STEP Software.

Yet many organizations continue to overlook one of the most valuable sources of diverse thinking available to them: neurodivergent professionals.

While businesses compete for talent, navigate increasingly complex technology environments, and search for new ways to innovate, many leaders are discovering that neurodiversity is not simply a DEI initiative; it’s a misunderstood business opportunity.

With July being recognized globally as Disability Pride Month, we felt July was the month we should be talk about neurodiversity in tech.

What is Neurodiversity?

Neurodiversity refers to the natural variation in how people think, learn, process information, and interact with the world.

Neurodivergence is a spectrum. The 11 most common presentations of neurodiversity include: ADHD (Attention Deficit/Hyperactivity Disorder), ASD (autism spectrum disorder), dyslexia and a handful of other differences.

The key word here is difference.

Neurodiversity is not about viewing individuals as problems to be solved. It recognizes that different ways of thinking can create unique strengths and perspectives. We touched on some of these unique perspectives back in April on our blog Down The Rabbit Hole: Why Business Leaders Should Lean in To Technical Deep Dives.

By the Numbers

According to Deloitte, approximately one in five adults may be considered neurodivergent, making neurodivergence one of the largest and often least visible forms of workplace diversity. CHADD.org research has estimated the general prevalence of ADHD in US adults at about 15.5 million, while dyslexia impacts 1 in 10 people globally, with over 40 million being US adults.

Co-existing conditions among the neurodiverse community is quite common, in fact, 50% of folks with ADHD also have dyslexia. In the era of highly competitive recruitment efforts for top IT talent, structuring hiring and retention practices to embrace neurodiversity becomes a competitive advantage.

Why Neurodiversity Matters for Technical Teams

Technology projects thrive on creative problem solving.

Software development, cybersecurity, quality assurance, data analysis, systems architecture, and engineering all require individuals who can identify patterns, analyze complexity, and approach challenges from multiple perspectives. The ability to hyperfocus (ADHD) and think visually (dyslexia) are power strengths within the software development community, especially when hunting down an illusive bug or designing a complex software architecture.

Deloitte research found that teams including neurodivergent professionals in certain roles can be up to 30% more productive than teams without them. Organizations also reported improvements in innovation, morale, and problem-solving capabilities. Some of the world’s biggest tech companies (Microsoft, SAP, IBM) are embracing the ‘Neurodivergent Movement’ with hiring initiatives and programs.

Why? Because neurodivergent professionals often demonstrate strengths in:

• Pattern recognition
• Attention to detail
• Deep focus on specialized topics
• Creative problem solving
• Systems thinking
• Visual thinking
• Process optimization

Its important to note, these strengths vary by individual. Neurodivergent people are not a monolithic group, and assumptions should never replace conversations about individual skills and preferences.

Common Misconceptions Continue to Create Barriers

One of the biggest challenges facing neurodivergent professionals is not capability, its perception.

Many organizations still rely on hiring and management practices that unintentionally reward social conformity over job performance. For example, traditional interviews often place significant emphasis on eye contact, conversational style, networking ability, and rapid responses. These factors may have little correlation to success in highly technical roles.

Discussions on Reddit frequently highlight concerns from neurodivergent workers who report being judged on communication styles rather than technical competence. Several software professionals describe losing opportunities due to perceived ‘culture fit’ concerns despite strong technical qualifications.

The misconception that neurodivergent employees require excessive accommodation is also often overstated. In fact, research supports findings that 49.4% of accommodations incur no cost at all, with the median cost being $300/employee or less than the cost of a static IP address for a fiscal quarter.

Research suggests that many accommodations designed to support neurodivergent employees can also improve workplace effectiveness for everyone. Clear communication, better documentation, flexible work arrangements, and thoughtful onboarding benefit all employees.

The Reality of Workplace Discrimination

Despite growing awareness, many neurodivergent employees continue to face discrimination and stigma. In fact, 65% of neurodivergent employees fear discrimination from management and as such often neglect to request accommodations.

Some workers report concerns about disclosing diagnoses due to fears of career limitations, bias, or exclusion, while others describe feeling pressured to ‘mask’ their natural behaviors to fit workplace expectations.

Masking has direct implications on employee wellbeing, and can lead to burnout. As we discussed in our Mental Health in IT blog, burn out is becoming a real problem in IT. Constantly hiding aspects of oneself can contribute this and disengagement.

Discrimination in any form is a ticking timebomb for workplaces and should be considered as serious a risk as cybersecurity threats.

Legal Responsibilities and Workplace Protections

Creating an inclusive workplace is not simply about compliance. It is about ensuring talented employees can perform at their best without unnecessary barriers.

In Canada, employees are protected under the Canadian Human Rights Act, which prohibits discrimination based on disability and requires employers to provide reasonable accommodations up to the point of undue hardship. The Government of Canada’s guidance on workplace accommodation emphasizes removing barriers and creating equitable access to employment opportunities.

Similar protections exist in many jurisdictions worldwide, including the United States through the Americans with Disabilities Act and throughout much of Europe under national disability and employment legislation.

The Diverse Human Advantage

In our recent blog Humans in an AI Time, we discussed how organizations increasingly need qualities that technology cannot easily replicate: creativity, judgment, empathy, and diverse perspectives, business acumen.

The most successful technology teams of the future are unlikely to be those where everyone thinks the same way. They will be teams that embrace different perspectives, different problem-solving approaches, and different ways of experiencing the world.

For business leaders, the opportunity is clear.

Building neuroinclusive workplaces is not simply about doing the right thing. It is about unlocking talent, improving innovation, strengthening teams, and ensuring that the people behind technology can contribute their best work.

In an industry built on solving difficult problems, diverse ways of thinking may be one of the most valuable competitive advantages available.

Drop us a line if you, or your team is stuck on a difficult problem, we’d be thrilled to offer our diverse perspective.

The post It’s Time to Talk About Neurodiversity in Tech first appeared on STEP Software.