Why AI Won't Replace Agile (But Might Help Us Rethink It)

Over the past few months, I've had more and more conversations (and read more and more) about AI "replacing" Agile roles. The latest, with a twist, is from Freya H Finnerty with Enfuse Group | B Corp™ .

Tools that promise to write your backlog, auto-generate a roadmap, or prioritise stories in a click. It's impressive. Sometimes even helpful.

But let's not get confused. Agile was never about the backlog. Nor the ceremonies.

And AI isn't the problem. Misunderstanding what Agile is for, now that's the real issue.

The Spectacle vs the Specific

I was chatting yesterday with award-winning author, fellow agilist, and CTO Giles Lindsay about the growing "anti-Agile" sentiment. You've probably seen it too: organisations questioning Agile's value, especially in uncertain times, what with growing economic pressure, political instability, global conflict. Then add AI into the mix, and suddenly agility feels… old?

But here's my twisted perspective. AI is evolving fast. And yes, it holds real promise. But many businesses are still stuck trying to "solutionise" with it, grabbing the tech before defining the problem. (You'd think we'd have learned by now. I've seen this game play out every year for the last 3-decades with the favoured tech of that year.)

The result? Inflated expectations. Misfired investments. The spectacle of AI, rather than the specificity.

I suspect we're on the cusp of a correction. Away from hype cycles, and toward durable architectures and useful applications. Stock market valuations are already showing signs of that shift.

Agile Isn't Broken. It's Misunderstood

Meanwhile, Agile has quietly been doing what it was always meant to do: helping humans make sense of complexity together.

Not writing stories. Not filling up Jira.

But creating shared understanding. Navigating ambiguity. Building alignment through conversation and iteration.

The latest Forrester "State of Agile" report (2025) reveals that 90% of organisations still believe in Agile's long-term value. Yet many senior leaders believe they've "done Agile." Ticked the box. Embedded it enough to cope with volatility.

Except, most haven't. Not really. Certainly from my observations and discussions this year, they haven't.

Because the real work of agility. The thinking, learning, adapting, aligning, isn't automatable by AI or any other technology solution.

The Misconceptions That Hold Us Back

In my conversations over recent months, I've noticed several persistent misconceptions about Agile's purpose that are actually hindering its potential in complex environments:

• "Agile is about going faster." Wrong. Agile is about learning faster. Sometimes that means slowing down to ask better questions or change direction entirely. Speed without learning is just accelerated failure (look at most AI initiatives for evidence).
• "If we follow the ceremonies, we're agile." The rituals without the reasoning create cargo cult agility. I've seen organisations religiously hold daily standups while completely missing emerging risks, or run retrospectives that never surface the real impediments.
• "Agile scales through frameworks." Frameworks can help, but they're not magic. True agility scales through aligned autonomy; those teams making good decisions because they understand the broader context, not because they're following prescribed patterns.
• "Agile means less planning." Actually, agile means more frequent, more responsive planning. The difference is planning for learning and adaptation rather than compliance to a fixed schedule. This includes strategy (nod to the great work some of us on the Agile Business Consortium 's Business Agility Think Tank are doing on Adaptive Strategy)

These misconceptions create organisations that look agile on the surface but remain brittle underneath. Exactly when complexity demands the most adaptive, resilient capacity.

Why Agile Coaches, Product People, and Teams Still Matter

AI may streamline tasks. But it won't replace:

• The moment a team feels stuck and someone asks the question that unlocks it.
• The tension in a retro that signals something deeper needs surfacing.
• The intuitive leap a product person makes when they reframe a customer need.
• The courage to stop a delivery train that's speeding in the wrong direction.
• The ability to sense when the framework is becoming more important than the outcomes.

That's the human work. And it's the heart of agility.

How Do We Navigate Through All of This?

So how on earth do we make sense of AI hype, agile misconceptions, and genuine organizational complexity—all at once?

This is exactly why I developed the CIRCA-CLEAR meta-framework. It's designed to help leaders navigate complex transformation landscapes where multiple forces are at play simultaneously.

CIRCA helps us understand the context we're operating in:

• What kind of complexity are we actually facing?
• Where are the real constraints and leverage points?
• How do emerging technologies like AI fit into our broader strategic landscape?

CLEAR provides the pathway forward:

• Clarity about what agility means for your specific context
• Learning systems that adapt faster than the environment changes
• Engagement that builds genuine capability, not just compliance
• Alignment that creates coherent action across the organization
• Results that compound over time

The beauty of this approach? It doesn't matter whether you're dealing with AI adoption, agile transformation, or any other complex organizational challenge. The same principles apply: understand your context first, then design your response accordingly.

Most organizations skip the context part and jump straight to solutions. Whether that's implementing AI tools or rolling out agile frameworks. But without understanding the specific complexity you're navigating, you're just adding more moving parts to an already chaotic system. Undoubtedly you've witnessed this as I have.

What This Means for Complex Environments

In genuinely complex environments (where cause and effect are unclear, where emergence matters more than prediction, etc.) these human capabilities become even more critical.

AI can process patterns from the past, but navigating complexity requires the ability to sense weak signals, challenge assumptions, and create new possibilities that no algorithm could anticipate.

The organisations that thrive won't be those that automate agility away, but those that use AI to handle routine tasks so humans can focus on the high-value work: sensemaking, alignment, and adaptive response.

What Now?

We don't need to fear AI. Nor do we need to defend Agile like zealots.

But we do need to help organisations rediscover what agility is actually about.

Not methodology.

Not mechanics.

But momentum through meaning. Clarity through conversation. And decisions that emerge from context, not templates.

Start by asking your organisation: Are we using Agile to go faster, or to learn better? And how does AI fit into that learning system?

The answer will tell you whether you're ready for the complexity ahead. Also whether you have the navigational tools to get there.

That's not going away. It's becoming more essential than ever.

The CIRCA-CLEAR framework helps organizations navigate complex transformations by understanding context first, then designing adaptive responses. Best of all, I've made it freely available under Creative Commons license. If you're wrestling with how AI, agility, or organizational change intersect in your specific situation, let's talk.