Everyone's Adding AI. Few Are Ready for It.
It’s hard to go a day without hearing about AI revolutionizing how we work. From strategy decks to product roadmaps, AI is being positioned as the great unlock, speeding up decisions, automating tasks, and transforming business models.
And to be clear: I believe the potential is real.
AI can amplify human capability, streamline operations, and uncover insights we could never see before. But there is a problem quietly playing out in boardrooms and backlog review sessions across the world:
Organizations are reaching for AI without fixing the foundations that make it effective.
The result? Fragmented pilots. Shadow tools. Confused ownership. Duplication. More noise, not more value.
AI Isn’t a Shortcut Around Good Team Dynamics
The rush to “do something with AI” often skips a more uncomfortable question:
Do we have the right team dynamics and interactions to make the most of this technology?
Most don't.
They’re still operating with:
Teams defined by internal functions, not user outcomes
Multiple versions of the same capability owned by different groups
Decision-making slowed down by layers of approval or unclear accountability
Data scattered, duplicated, or inconsistently maintained
And when you pour AI into that mix?
You get acceleration, but of dysfunction, not progress.
Before AI, Understand Flow
The value of AI doesn’t come from the model alone. It comes from how AI connects to your flow of value, how your teams sense needs, act on them, and evolve together.
AI becomes another disconnected tool if those loops are broken or unclear. That’s why, before layering in new technology, leading organizations are asking:
Where are the current sources of friction in our delivery?
Which parts of our system are slowing feedback, learning, or action?
Where do our teams struggle to own or evolve what they deliver?
These aren’t technical questions. They’re ones about organizational dynamics.
Foundations First: What to Do Instead
If you want to use AI well, really well, start by strengthening the foundations it depends on.
Here are three places to begin:
1. Map Where the Work Flows (and Where It Doesn’t)
Most friction doesn’t show up in the sprint review. It hides between teams, in unclear handovers and implicit ownership.
Map your work from user need to outcome. Identify where things get stuck, duplicated, or reinterpreted. That’s where AI might help, or where it might make things worse if left unresolved.
2. Clarify Capabilities and Ownership
AI often crosses boundaries: data here, logic there, outcomes somewhere else.
Make sure the teams responsible for those capabilities know who owns what. If you have multiple teams solving the same problem in different ways, AI will only widen the gap.
3. Start with Needs, Not Novelty
Ask your teams:
Whose problem are we trying to solve?
What outcome do they need?
What’s blocking that outcome today?
Then ask whether AI helps, and if so, how, where, and with whom.
That’s where real value starts to emerge.
The Upside of Getting This Right
When you get the team dynamics right, AI doesn’t just feel like another transformation project. It becomes part of how your organization senses, learns, and evolves.
You create teams that:
Can experiment safely and align quickly
Know where AI fits, and where it doesn’t
Own their outcomes and adapt their capabilities over time
That’s not just AI readiness. That’s strategic agility.
A Final Thought
AI won’t fix your team dynamics. But it will expose it.
If you want to unlock the promise of AI, don’t start with a model. Start with your org chart, your team boundaries, your decision loops, and your delivery friction.
That’s where the real work begins.
If you would like help making AI more effective in your organization by introducing better team dynamics, DM me.
