It probably isn’t, right? Millions of authors on the topic, expansive data center builds, government policies, wild valuations … could they be wrong? The truth, as it usually is, is that this is somewhere between “This will change everything” and “This will do nothing new. I’m bored. What’s next?”

But … what if?

The AI market right now looks less like a strategy discussion and more like a land grab with better branding. Every company is sprinting, every board is asking the same question, and every vendor is waving a map that conveniently leads right back to their product. This is not new territory. We have seen this movie before in cloud, in digital, in mobile, in the early days of the internet. What is different this time is the speed, the scale, and the number of participants. This means (as it did for cloud, etc.) a paramount concern in these early days is cost control during attempts to scale.

Why is this the case? Is it because we’ve been primed by Hollywood for decades that robots will take over the world? Now that they are “here” (debatable), do we feel unrelenting pressure to have the best robot faster than everyone else? (Do I really need an agentic-enabled refrigerator?) When everyone feels behind at the same time, discipline disappears, urgency becomes an excuse for poor judgment, and organizations start approving investments they cannot explain and deploying capabilities they cannot support.

You want a fast path to losing the trust of your business partners? This is how it happens. Take a different path!

Be Intentional About Architecting For Business Agility

Simply applying industry buzzwords may help achieve a degree of technical agility, but truly architecting for business agility requires a few changes in mindset:

  • Focus on business design, not merely technology. Forrester frames its vision for business design and the future of solution architecture around software-based business building blocks that allow rapid reconfiguration of business to deliver new business transactions, enhance business process, meet the demands of customers and employees with optimized digital experiences, provide timely insights for business decisions, and otherwise mirror the ways that business changes in the structure of one’s software.
  • Center on structure first, technology second. Developers should focus first on the structure — specifically, the business structure — of what they are building. They should then place technologies and implementation patterns, whether APIs, microservices, low-code platforms, cloud integration, process automation, artificial intelligence, machine learning, mobile, or any other buzzword-compliant technology, within the software structures framed to deliver business building blocks.
  • Place APIs and services as foundational investments. Integration requires more than APIs, and agile apps require more than services, but both APIs and microservices have broad-based, pervasive applicability to a wide range of business and technical scenarios. Thus, both deserve a foundational place in one’s architecture strategy to foster business agility.
  • Go beyond industry headlines to craft deep and rich technology designs. Neither industry headlines nor simplistic, dogmatic guidelines provide the depth and richness of design thought needed to craft API designs or microservice platforms that deliver robust business integrity — which is still needed to deliver excellent customer experience. Sure, customers won’t so much care if quickly delivered software results in a recommendation box showing an irrelevant product, but just ask a mobile banking app user if they care whether their money transfer transaction gets correctly processed by the underlying microservices and APIs. Crafting the right quality of service for the right place in the software is a critical part of business design, and that requires deep skills and carefully executed solution architecture.

Sound familiar? If you are a long-time Forrester reader, you’ll know we wrote the text in this section in 2017 — about microservices. Therefore, I refer you to our more recent research on these topics as opposed to reading this section for any new thinking on our part!

So What Should Tech Leaders Do About It?

The question, therefore, is quite simple: What if AI turns out to just be the next in a long line of technology advancements? Robotic process automation was going to turn bots loose on automation in your core systems, with a dramatic ROI, while definitely not breaking anytime the UX changed. Cloud promised super-low cost, easy to just move your workloads from your data center without replatforming. Service-oriented architecture was going to be the path forward for modernizing your legacy debt by modularizing key processes, orchestrating across these processes, and landing on more robust systems of insight and engagement.

I’m still waiting for my digital self in the metaverse to go to all my boring appointments for me. Any of these also sound familiar? How did they work out? Somewhere in the middle, right?

If this is, in fact, just another turn of the crank in a very long machine, then tech leaders need to both push hard on the rest of the C-suite searching for a magic, quick answer while continuing to be the disciplined operators who have seen a few cycles and learned something from them, because the real risk is losing control of the basics while chasing it, approving spend that cannot be defended, scaling workloads that cannot be supported, and handing business partners a bill without a story that makes sense.

Treat AI like any other high-potential, high‑noise technology, where the winners separated themselves by doing the boring work well, which means demanding a clear value narrative before funding, insisting on operational readiness before scaling, investing in people and data, and putting guardrails around experimentation so curiosity does not quietly turn into cost. Hold your teams to evidence, not enthusiasm, and force every use case to stand on its own merits with transparent outcomes and accountable owners, because credibility with the business is earned in moments like this when everyone else is sprinting on vibes.

The tech leader who comes out ahead is the one who keeps their head while everyone else is chasing the latest promise, makes deliberate bets they can explain in plain language, and proves that speed without discipline is just a faster way to lose trust.

It would be foolish to blindly assume that AI is just the latest trend and not any different. Continue to push for productivity gains where it is already effective (i.e., summarization) while exploring ways to experiment with possible foundational shifts. If it is, however, then doing the boring work is still a “no regrets” investment that will benefit your company in many other ways.

Forrester has a full team of analysts covering the topic of AI from all angles. Schedule a guidance session with us if you’re a client or leverage Forrester AI for instant insight.

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