AI won’t replace your job, but it will expose which parts of it truly matter.
AI isn’t coming to take your job. But it is coming for some of the parts of your job that you don’t love. Don’t worry, everyone has parts of their jobs that they consider less than ideal…I’m not going to tell on you to your manager. It’s also here to help you improve upon the aspects of your job that you do like. That’s the real shift. Personally, I thoroughly enjoy using a variety of AI tools to put structure around the creative processes that feed the Solution Design engine that I call my mind.
For years, enterprise work depended on us humans acting as connective tissue. We would spend time writing requirements documents, explaining and re-explaining decisions, and stitching together intent across handoffs. Not because it was valuable work, but because the lack of tools forced it…we had no choice. AI changes that dynamic.
Speed Without Stakes
Usain Bolt, Mikaela Shiffrin, Lewis Hamilton, AI. What do they have in common? They are very fast. AI is very good at speed. It can summarize conversations instantly, generate designs on demand, produce artifacts faster than any team ever could. What it can’t do is judgement.
AI doesn’t understand organizational nuance. It doesn’t understand what happens in the room. Picture this: you’re in a cross‑functional status meeting on a project that’s already delayed. On paper, everything sounds aligned, but in reality, the work has already failed emotionally.
Nobody objects because nobody believes objecting will change the outcome. Trust isn’t just thin…it’s irrelevant. The plan has lost credibility, so people disconnect immediately. They disengage early, hedge their effort, and wait for direction instead of shaping it. By the time delivery begins, the organization has already moved on.
AI can summarize the meeting perfectly and still miss the most important truth: people have stopped believing this is worth their energy. What makes that even harder to recover from is the fact that AI can’t invest in the outcome either. Understanding is one thing, but investment is another. The humans in the room may have disengaged, but they chose to be there. At some point, they had skin in the game. They carried the weight of ownership, even if that weight is exactly what crushed the initiative’s momentum.
AI has no such stake. It will generate the next version of the plan with the same enthusiasm it generated the last one. Everyone out there reading this who has interacted with AI can attest to that…everything is “Great Idea!”, even if the idea is terrible. It’s almost as if it’s afraid to disagree with you and make you sad. It doesn’t lose sleep over whether or not the initiative succeeds. It doesn’t feel the accountability that comes with having pushed for and lost on a particular approach. Worse, it simply doesn’t care. That absence of personal commitment isn’t a flaw in the AI, it’s just what it is.
That means the humans around it have to carry that investment more intentionally than ever. Someone has to be the one who actually cares whether or not this works. Someone has to own the outcome, not just the output.
The Work That’s Actually Disappearing
The biggest mistake people make is assuming AI replaces people. It doesn’t. It replaces late‑stage translation. You may be saying to yourself “Hey Jay, what’s late-stage translation?” I’m glad you asked. Late-stage translation is the work of explaining, documenting, and re-expressing decisions after they’ve already been made.
When AI can generate outputs instantly, the value moves upstream. The most important work now happens before decisions harden, while assumptions are still flexible and direction can still be fluid enough to change.
Roles that were built around explaining decisions after they’re made start to fade. Roles built around shaping decisions before they’re locked in become critical. That’s the rewrite.
Why the Early Moments Matter More Than Ever
As development and delivery accelerate, there’s less room for remediation. There’s even less tolerance for rework. And there’s probably no more patience for “we’ll fix it later.” This is all great, but it puts pressure on the earliest moments of the lifecycle.
The people who thrive aren’t the ones producing the most artifacts. They’re the ones asking better questions, raising up red flags early, and helping teams make smarter choices before accelerating them further with AI.
Those aren’t technical skills. They’re human ones.
Where the Solution Designer Fits
In my previous post, I talked about the rise of the Solution Designer. AI is the fuel to that rocket ship.
Now that design has become faster and cheaper, someone has to ensure speed doesn’t come at the cost of intent. Someone has to guide AI toward the right outcomes, not just the fastest ones. Someone has to rise to the pressure that exists when everything is still malleable, decisions are still formulating, and getting it wrong is far more expensive than getting it late. Someone who understands that pressure is a privilege, as Billie Jean King put it.
That’s the Solution Designer. Not competing with AI, directing it.
Where Human Value Compounds
If your role depends on documentation, explanation, or translation, AI will absolutely change how you work. But if your value comes from insight, facilitation, and judgement, AI gives you that leverage you’ve always looked for…not competition.
The future doesn’t belong to one type of role or skill set. It belongs to teams where deep technical expertise and strong decision‑making work together, where technology is applied deliberately, in service of the right outcomes.
What Comes Next
So if AI is rewriting roles, rather than replacing them, what does that mean for discovery?
In my next post, I’ll explore how discovery itself is changing, and why the most important pre‑sales skill now isn’t explaining solutions, but turning discovery into something teams can actually build from.
Because in an AI‑driven world, clarity isn’t a document, it’s a design baseline.