We tend to think of AI as a gift to tech teams – helping folks write code faster, automate tests, and analyze data like wizards. And sure, that’s happening. But if you zoom out a bit, the most immediate and surprising gains from AI aren’t showing up in Git commits or deployment pipelines. They’re showing up in inboxes, spreadsheets, meeting notes, and yes – PowerPoint decks.
In other words, the real ROI of AI isn’t tucked away in the guts of your tech stack. It’s happening on the business side, where folks are using AI to do more work in less time, with fewer headaches. That shift – from tech pros to everyday business users – is worth paying attention to.
Let’s start on the engineering side. Developers now have AI tools that can autocomplete code, write test cases, or suggest design patterns. GitHub Copilot, CodeWhisperer, and friends are helpful, and they’re improving daily.
But here’s the thing: for most tech teams, this feels more like a tooling upgrade than a revolution. Helpful? Absolutely. Transformative? Sometimes. But it still requires context, oversight, and technical nuance. And adoption moves at the speed of process change – which, as you know, is...not always lightning fast.
Now let’s look at the other side of the house.
Give a finance lead or HR partner access to something like Microsoft Copilot, ChatGPT, or Notion AI, and suddenly they’re summarizing meetings, drafting communications, analyzing reports, and building decks in a fraction of the time. No code. No IT ticket. Just results.
This is where the real momentum is. Business users aren’t just dabbling – they’re shifting entire workflows. And they’re doing it faster than most technical orgs can deploy a new internal tool.
In DevOps, we talk about “shifting left” – moving things like testing and security earlier in the development cycle. But AI is doing something different. It’s shifting right – closer to the edge of the organization, where work actually gets done.
The power of AI is no longer bottled up in R&D or tech teams. It’s landing directly in the hands of the folks running your ops meetings, drafting policy docs, managing client relationships, or forecasting budgets.
They don’t need to wait on IT. They’re building better workflows today.
It’s tempting to look at AI investments through a technical lens: smart features in your app, machine learning for predictive analytics, all the buzzwords. That stuff matters – but it takes time, talent, and runway.
Meanwhile, enabling business teams with off-the-shelf AI tools delivers results in weeks, not quarters.
The smartest move many leaders can make right now? Invest in helping your people get good at using AI. Run workshops. Bring in consultants. Let teams experiment. You’ll see measurable impact faster – and you’ll build an organization that’s more adaptable by design.
If you’re in a leadership role, here’s the nudge: don’t gatekeep AI behind technical roles. Encourage experimentation across your organization.
Some of the best use cases will come from folks closest to the real problems – not the ones writing code, but the ones trying to keep a department running smoothly on a Tuesday afternoon.
AI is a tool. The best ROI comes from getting it into the hands of the people who are ready to use it creatively. And more often than not, those people aren’t in your engineering standups. They’re in your revenue meetings, ops reviews, and internal project threads – ready to move fast, if you let them.
If you are struggling with a plan to securely adopt AI tools for business and technology teams, Trility can help.
