Transcript
AI does not eliminate teams.
It increases the need for great ones.
The faster a team moves, the more collaboration the team requires.The more productive individual contributors become,the more their work needs to be coordinated.
And the powerful AI becomes as a tool, The more dangerous it is when someone uses it in isolation.
Put simply, AI amplifies everything, including misalignment.
Unfortunately, many teams are responding to AI by collaborating less, and that is where things begin to fall apart.
Over the last few years, I've watched teams adopt AI tools in ways that unintentionally reduce communication.
Developers can now accomplish huge amounts of work on their own.
Product owners can use AI to generate and split backlog items, or even prioritize entire roadmaps.
teams start to believe they no longer need to talk as often because the tools are doing so much of the work.
The theory goes, if AI can generate stories, code, and tests, perhaps the team can get by with fewer discussions.
the reality is very different.
I've seen teams that, excited by AI's efficiency, quietly slip into working as a collection of individuals rather than as cohesive unit.
They may hold the same meetings, but the communication within those meetings becomes thin and surface level.
Outside the meetings collaboration dwindles even further.
AI is not just speeding up development.
It's reshaping what the key roles inside Agile teams actually do.
These changes are significant, and understanding them helps us understand why collaboration remains so important.
Product owners may be the biggest beneficiaries of AI in the short term.
AI can help them write backlog items, generate acceptance criteria, analyze customer sentiment, summarize research, even propose priorities.
For a role that has always struggled with having enough time to do the job, this is a welcome change.
But with that support comes temptation.
It becomes too easy to delegate too much thinking to an AI.
A product owner who lets AI drive backlog prioritization or roadmap decisions risks drifting away from customer needs, business realities,
and strategic intent.
AI can assist, but it cannot own core decisions such as product vision, market positioning, customer segmentation, or business models.
I've seen product owners who let the AI do most of the heavy lifting only to discover later that the product had wandered off course.
It's an example of how AI could be a powerful assistant but a poor navigator.
For years, I've believed the Scrum Master role would inevitably shift as teams became more experienced.
As a team becomes proficient with Sc rum, team members absorb some of the responsibilities of a Scum Master.
AI is accelerating that shift.
The future Scrum Master is less of a process guardian and more of human dynamics expert.
They will likely work across multiple teams, operate part-time on any single one, and spend far less energy worrying about prescriptive frameworks.
Instead, they will focus on helping people work well together, asking tough questions, facilitating constructive disagreements,
guiding the team through difficult decisions.
These human-centric skills will define the role.
Scrum Masters and Agile coaches who cling to checklists and frameworks will become less effective.
Those who cultivate emotional intelligence, facilitation skills, and the ability to coach collaboration will be essential.
I've seen Scum Masters who remain overly focused on rituals and mechanics while their teams quietly slide into dysfunctional communication patterns.
In an AI-driven world, that approach won't work.
Developers have also experienced extraordinary leaps in productivity.
AI helps them generate code, uncover bugs, explore architectural patterns, and write tests.
This enables them to accomplish far more in less time.
And with that increased capacity comes a shift in team design.
Many products that previously required teams of eight might now effectively be built by teams four or five.
This shift also changes how teams think about specialization.
We will still need world-class experts for highly specialized problems, but many teams will rely on strong generalists who possess broad skills and deep
AI fluency.
It also means that developers, moving faster than ever, must communicate more frequently to avoid stepping on each other's work.
AI accelerates their capabilities.
Human alignment ensures those capabilities don't create chaos.
All of these changes point toward a future where agile teams look different than they did even a few years ago.
I expect teams to become smaller and more fluid.
In many organizations, team membership will include a stable core supplemented by temporary specialists who join for a couple of weeks or months to work
on highly complex tasks before moving on.
Teams will also continue to become more globally distributed, though work from anywhere of movement has only strengthened,
and AI will make collaboration across time zones even easier.
Yet, despite these changes, the definition of a team should remain simple.
A team is a group of identifiable people pursuing a shared goal.
That definition still holds, even when membership becomes more fluid.
As AI lowers the cost of experimentation, teams will attempt more ideas, pursue more niche products, and pivot more quickly.
This makes leadership more, not less, important.
Leaders must provide direction, so experimentation does not devolve into chaos.
Leaders set strategic intent, define boundaries, and articulate a North Star that teams can use as an anchor.
Since AI accelerates work, the practices that hold teams together become even more essential.
The Sprint Review is one of them.
As AI speeds up delivery, ensuring alignment between what the team builds and what stakeholders expect becomes absolutely critical.
Only through real human feedback and the interpretation of that feedback can teams ensure that AI-accelerated work remains on target.
Backlog refinement is another practice that must remain human-led.
AI can draft backlog items or propose ways to split stories.
But only humans can decide if those items contain the appropriate amount of detail, whether the intent is right, and whether each aligns with the product vision.
Daily communication becomes essential as teams move faster.
That communication doesn't need to be in a formal meeting.
Many teams will choose asynchronous check-ins rather than a traditional daily scrum, but the keys are frequency and consistency.
When a team can build features in hours, they need talk about what they're doing more often, not less.
Iteration planning is similarly indispensable.
Even if AI assists in forecasting, the team must align on intent and understand how their work fits together.
Planning keeps the teams grounded in shared understanding.
The common thread is simple.
AI accelerates work.
Collaboration prevents accelerated mistakes.
Teams that reduce collaboration as AI usage increases will eventually undermine the very speed they're trying to gain.
Leaders often ask how they'll know whether AI is helping or hurting their teams.
The answer doesn't require a dashboard full of metrics.
It comes down to this simple question.
Are team members communicating more frequently than they did before AI?
If communication is decreasing, collaboration is weakening, and teams are heading into danger.
the faster the team moves, the more essential communication becomes.