Tunde reports 88% of organizations are experimenting with AI, 36% see P&L impact, but only 6% see major benefits. The shift from piloting to scaling is happening now. Key is reimagining work and managing token costs. AI is likely to increase hiring overall, not reduce it, with a 6-12 month lag.
Asks about the state of AI adoption in European enterprises, given cost concerns.
Tom
Tunde Olanrewaju
88% experimenting, 36% see P&L impact, 6% see major benefits. The real story is shifting from experimentation to scaling.
Cost of cognition has dropped dramatically, driving adoption.
Asks whether this is the year of scaling from piloting.
Tom
Tunde Olanrewaju
Yes, the time is now. Last year was about access; this year is about fundamentally shifting how work is done.
Asks about buying smartly to manage token costs and using the right model for the job.
Anna
Tunde Olanrewaju
Two key things: reimagining the work (e.g., 2 developers + 10 agents) and managing token economics. Frontier models can be 10-100x more expensive than cheaper models.
Asks about organizational structure changes needed for AI.
Anna
Tunde Olanrewaju
Businesses organized around rationing expertise; AI makes expertise cheaper, so structures like escalation hierarchies need to change. E.g., one manager + 300 AI agents instead of 20 people.
Asks what needs to happen to move from 6% seeing major benefits to 20-40%.
Tom
Tunde Olanrewaju
Imagination and picking the right places. Software development is already transforming; customer contact is next (chatbots replacing browsing).
Asks about job cutting as part of efficiency gains.
Tom
Tunde Olanrewaju
History shows technology doesn't reduce aggregate employment. Data from Ramp/Revelio shows companies spending more on AI hire more workers (6-12 month lag, ~10% more).
There will be shifts and transitions, but overall more types of work will emerge.
