The Future of Agility: Artificial Intelligence, Friend or Foe?
Understanding AI's Role in Transformation in 2025
In the second panel session on the future of agility, one topic drew sharper focus than almost anything else: Artificial Intelligence. Is AI a partner in driving agility forward, or a looming disruptor set to overhaul how we work?
The reality is, AI is already reshaping agility. But its role is more nuanced than a simple good versus bad. The real shift lies in how we choose to integrate it.
AI and Transparency: Goodbye to Middle Management-as-Reporting Layer
Several panellists highlighted that many roles traditionally acted as information gatekeepers. Status reporting, escalation, and dependency management often made up a large part of middle management's responsibilities. With AI providing real-time visibility across portfolios, roadmaps, and even team health, some of these layers become less essential.
The future isn't about "replacing people," it's about removing bureaucratic friction. This frees up human energy for creativity, innovation, coaching, and leadership — things AI can't (and probably shouldn't) do.
Accelerating Delivery, Not Diminishing It
Another point raised: AI can turbocharge refinement, prioritisation, and dependency mapping. Think about story writing, backlog grooming, or design prototyping. Where once a backlog session might take hours, assisted workflows can surface better stories and insights faster, leaving teams more time for high-value collaboration.
Importantly, AI enhances human decision-making rather than removing the human. Models still need validation. Priorities still need business context. Alignment across teams still needs leadership.
New Skills for a New Era
Agility professionals won't be replaced, but they will need to evolve. Understanding prompt engineering, data literacy, and AI ethics will be as important as knowing how to run a retro or manage a portfolio.
Agile coaches and leaders must now also coach humans and systems — ensuring the way we use AI aligns with outcomes, not just outputs. It's a new domain for stewardship.
The Risk of Hype and Theatre
AI itself won't solve cultural resistance, unclear strategy, or lack of leadership buy-in. If we think "sprinkling AI" into bad agile practices will fix them, we're setting ourselves up for the same theatre that diluted agility in the first place.
Several panellists warned against "AI-washing" transformation efforts, where executives simply rebrand their agile or digital initiatives with an AI label without meaningful changes in behaviour or governance.
Practical Examples Shared:
Teams using AI to generate backlog refinement options, then manually choosing what to prioritise.
Portfolio managers using AI to run dependency heat maps to surface bottlenecks faster.
Agile coaches co-piloting retrospectives with AI sentiment analysis but still facilitating the real conversation.
Where We Landed
AI is neither a friend nor a foe. It's a tool. How we use it will determine whether it fuels real agility or just accelerates the same old dysfunction.
The best transformation leaders will be the ones who stay curious, experiment responsibly, and keep their focus not just on faster delivery, but better outcomes for customers and teams.
And in that future, agility isn't dead. It's just evolving — again.