thanks to our new Imbila reader, Warwick M, who shared this piece from FT, “What a Soros theory can tell us about the AI boom”, and inspired this first post of 2026.
As we enter 2026, the AI conversation is changing.
For the past few years, much of the focus has been on the technology itself — new models, bigger chips, faster compute, eye-catching demos. That phase mattered. It built the foundations.
But the more interesting shift this year is simpler:
The AI infrastructure is now good enough for real business change to happen.
Not in theory. Not just in Big Tech. But inside everyday organisations.
From hype to usable infrastructure
Every major technology wave goes through a similar arc:
- Early excitement and experimentation
- Heavy infrastructure investment
- A messy period of confusion and overreach
- Practical adoption that reshapes how work actually gets done
AI has clearly moved into that fourth phase.
The tools are no longer experimental curiosities. They are:
- Embedded in productivity software
- Accessible to small teams, not just enterprises
- Affordable enough to test without huge risk
- Good enough to augment real human work
This is why the question has shifted from “Is AI real?” to “Why aren’t we using this more effectively?”
Why this moment matters for businesses of all sizes
Large organisations often move slowly, even when the opportunity is obvious. Smaller businesses, teams, and professional services firms have an advantage here: they can adapt faster.
The opportunity in 2026 isn’t about replacing people. It’s about:
- Freeing skilled teams from low-value work
- Improving decision-making with better information
- Redesigning workflows around human judgment + machine support
- Helping people focus on what they’re actually good at
This is where meaningful transformation starts — not with tools, but with how work is structured.
The role of AI consultants is changing
In this environment, the most valuable AI consultants aren’t:
- Tool resellers
- Prompt engineers
- Hype translators
They’re partners in business change.
The real work looks like:
- Understanding how a business actually operates
- Identifying friction, bottlenecks, and hidden manual effort
- Helping teams re-think roles, processes, and responsibilities
- Upskilling people so AI becomes an everyday assistant, not a black box
This is less about “implementing AI” and more about helping organisations use their people better, supported by machines.
A more useful mindset for 2026
Instead of asking:
- Which AI tool should we buy?
- Will this replace our team?
Better questions are:
- Where do our best people waste time today?
- Which decisions could be better supported with information?
- What work should humans always own — and what shouldn’t they be doing at all?
When those questions lead, the technology naturally follows.
Looking ahead
Every technology boom leaves behind powerful infrastructure. AI is no different.
What’s different this time is that the tools are already usable — and the gap between experimentation and impact has narrowed dramatically.
For businesses willing to engage seriously, 2026 is not about waiting for the next breakthrough. It’s about learning to leverage what’s already here.
And for those of us working with organisations, the opportunity is clear:
Help businesses use AI to amplify their people — not replace them — and real transformation can happen this year.