You’re Not Behind on AI — Everyone Else Is Just Pretending

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Product leaders everywhere feel the pressure to adopt AI.

But here’s the truth: most teams are still stuck.

At Atlassian’s Team ’25 Rovo dominated the conversation.

Everyone’s excited — finally AI adoption is within reach!

But few know where to start.

While executives and product leaders worry they’re falling behind, many competitors are quietly struggling with the same roadblocks.

Why do product organizations fail to adopt AI effectively?

🔍 Contextual blind spots — AI struggles with nuance: product strategy, historical tradeoffs, and team dynamics. PMs don’t need more answers; they need relevant ones.

📚 The knowledge mess — Integrating with “everything” sounds great… until you hit scattered, outdated, or undocumented content.

⚙️ Infrastructure ≠ solution — GenAI provides the plumbing. But teams still need prompting skills, agent design, and usable interfaces. Many “ChatGPT wrappers” fail because no one knows how to use them.

🧩 Too much friction — New tools = new tabs, new habits, new friction. PMs are already stretched thin; they don’t have time to relearn how to work.

🔒 Trust is fragile — One wrong AI-generated recommendation on scope, timing, or customer needs can erode trust instantly.

So, what’s the better path?

✅ Tools that surface context, not just guesses
✅ AI that asks smart questions, not just delivers answers
✅ Seamless integration into existing workflows — no extra tabs or new habits required

Rovo is exciting, but we need to remember that this is just the infrastructure we can built on top of.

That’s the mindset I’ve seen succeed — and it’s the same philosophy we follow when designing solutions like Wisary.

The future of AI in product teams isn’t about turning everyone into a prompt engineer.
It’s about creating better UX on top of AI — helping humans stay sharp, aligned, and effective.