AI isn’t the change – we are, together.
By Carl Sargeson
We’ve all seen the promises: AI-led transformation will reshape industries, redefine roles, and revolutionise how we work. But despite billions of pounds spent, 70% of organisations still don’t see measurable value (McKinsey). Why? Too often, transformation is done to people, not with them.
That’s where leadership, and engagement from the ground up, matters.
Ground-Level Insights into AI-led Transformation
From conversations with clients across sectors, a few consistent truths emerge:
- AI-led transformation pilots stall if teams feel unheard or uninvited
- Technology validates only when people feel confident using it
- Resistance often signals unanswered questions, not outright opposition
Sound familiar?
Why Bottom-Up Matters in AI-led Transformation
McKinsey’s research across hundreds of global transformations reveals a critical pattern:
When line managers and frontline employees are actively engaged, AI-led transformation success rates jump from under 3% to 26–28%, depending on the involvement level.
Their “transformation triangle” emphasises top-down direction, bottom-up improvement, and cross-functional redesign—all three areas must align for change to stick.
Bottom-up engagement isn’t fluffy.
It’s statistically proven to unlock both momentum and value.
AI-led Transformation Is a Capability Shift – Not Just a Tool Rollout
To get value from AI, your change strategy can’t be purely tech-first. It must:
- Start with use cases aligned with business goals
- Involve people in solving daily problems with AI, not prescribing tools
- Mobilise digital champions and frontline voices to lead experiments and normalise learning
That’s bottom-up leadership. And it works.
How to Weave Bottom-Up into AI-led Transformation
- Activate early adopters – then let them lead
Invite everyday users to try, tinker, and feed back insights. Use their examples to build trust across teams; build your change champions and advocate them. - Start small with MVPs, learn fast
Every successful organisation we’ve seen pilots one or two low-risk but meaningful AI-led transformation use cases first—often saving hours on admin tasks or summarising workflows. - Communicate the ROI AND address fear
When roles shift, people ask: Do I still belong here? Be clear on AI’s purpose, the benefits, and how tasks may evolve. - Empower mid-level leaders to own the change
Middle managers equipped with confidence and empathy are four times more likely to catalyse adoption. Support them with coaching, frameworks like the Change Curve, and space to lead.
Realigning the AI-led Transformation Conversation
Empowering people from the ground up doesn’t dilute leadership, it amplifies it. It turns pilots into practice and experiments into capability shifts.
That’s the kind of business change strategic leaders are navigating. AI-led transformation only lands when people, not just processes, are at the centre.
Join us in September to explore practical tools, frameworks, and debates around leading, engaging, and embedding change in real-world systems.
Because AI is accelerating disruption, but people still decide what sticks.
My Commitments to AI-led Transformation (So Far)
I’m not a tech lead. But I am an ‘AI Tourist’ trying to navigate fast change, and help others do the same. So, here are a few small things I’ve started doing to stay sharp and grounded with AI-led transformation:
- Carving out space to learn
Every Friday morning, I block 30 minutes to explore one AI use case—no meetings, no pressure. Sometimes I just play with a tool or try a new prompt technique. - Making the conversation safe and visible
I’ve started weaving AI check-ins into daily interactions. Simple stuff: “Have you seen anything useful lately?” or “Anything feel unclear or risky?” - Testing use cases where it matters to me
Instead of vague experiments, I’m focusing on real tasks, like summarising dense reports or drafting outreach copy. - Keeping myself honest
Every quarter, I reflect on where I might be missing something – biases in what I prompt, who I include in decisions, or which voices I listen to.
These aren’t revolutionary. But they’re real. And they keep me engaged with the shift—not just watching it go by.
