The Hardest Part of AI Transformation Isn’t the AI
After twenty years and
dozens of programmes, the technology was almost never the thing that decided
success.
I
have spent two decades leading transformation across the UK, India, and the
Gulf, through waves of technology that each arrived promising to change
everything. AI is the most powerful of those waves. But if you asked me what
actually decided whether a programme succeeded or quietly died, my honest
answer would rarely be the technology.
It
was almost always the people. The fear, the fatigue, the politics, the unspoken
resistance in the room. The hardest part of AI transformation is human, and we
under invest in it because it doesn’t fit neatly on a Gantt chart.
The programme that nearly failed
for no technical reason
I
remember a programme where every technical indicator was green. The
architecture was sound, the early results were strong, the business case held.
And it was dying. Not because anything broke, but because the people expected
to live with the change had never been brought along. They had been informed,
not convinced and there is an enormous difference.
The
turnaround had nothing to do with the platform. It came from slowing down,
sitting with the teams who felt threatened, and addressing the question nobody
had said out loud: what does this mean for me? Once that was answered honestly,
the same technology that had been stalling started to move.
People don’t resist change. They resist being changed
without being consulted. The distinction is everything.
Consensus is built in corridors,
not steering committees
Executive
alignment is real work, and it does not happen in the formal meeting. By the
time a decision reaches a steering committee, it has either already been agreed
in a dozen quieter conversations or it is about to be politely buried. The
leaders who get transformation through are the ones who do the corridor walk
listening, addressing concerns privately, building genuine consensus before the
vote, not during it.
The cost of change fatigue
Organisations
have a finite capacity for disruption, and AI is arriving on top of years of
other change. Push too hard, too fast, and you don’t get speed you get burnout, quiet sabotage, and the kind
of compliance that does the minimum and waits for you to lose interest. Pacing
a transformation humanely is not softness. It is how you actually arrive.
What I’d tell my younger self
Early
in my career I believed that if the solution was good enough, the people would
follow. They don’t. The solution is the easy part. Spend your energy on the
humans — their fear, their dignity, their need to be brought along rather than
dragged — and the technology will largely take care of itself.
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