The Real Cost of AI: It's More Than Just Tech

Agentic AI, the kind that acts independently to achieve goals, is often touted as the future of business. But what's the real story here? Beneath the glossy exterior, there's a hidden cost that's less glamorous: the continuous engineering work needed to keep these systems relevant and effective.

The Engineering Challenge

The true challenge isn't just deploying agentic AI, it's keeping it updated. Businesses operate on fragmented systems, think legacy software mixed with cloud solutions. For AI to function efficiently, engineers must constantly rebuild and recalibrate the AI's understanding of these ever-shifting landscapes. It's like trying to tune a piano while the pianist is playing a complex concerto. Not easy, right?

Let's be clear. This isn't about setting up AI once and reaping endless rewards. It's about ongoing investment in engineers who can bridge the gap between outdated systems and the AI's need for real-time data. And this ain't cheap.

Why Should You Care?

So, why does this matter to anyone outside the engineering department? Because it directly impacts the bottom line. Companies often buy into AI solutions expecting immediate ROI, only to discover that the real cost comes from the backend work that keeps these systems running smoothly.

The press releases herald AI transformation. The employee surveys, though, often tell another story. They're full of complaints about tools that don't quite work as promised. Why? Because the engineering effort to maintain them is underestimated or underfunded. The gap between the keynote and the cubicle is enormous.

Reevaluating Priorities

Is AI worth the hassle if it demands such relentless engineering attention? That's the billion-dollar question, and it's one more companies need to consider before diving in. If you're not prepared to invest heavily in ongoing maintenance, you're setting yourself up for disappointment.

Management buys the licenses. Nobody tells the team that those licenses are just the beginning, not the end of their AI journey. As companies move forward, clearer communication and realistic expectations about the continuous engineering demands of AI could save headaches and resources down the line.

The takeaway? If you're considering agentic AI, look beyond the initial investment. It's not just a question of whether you can afford it now, but whether you can afford to keep it running tomorrow.