After a year of pilots, lessons learned, and a few hard truths, 2026 is shaping up to be a very different year for AI.
Execs aren’t asking “what can AI do?” anymore.
They’re asking “what should we actually focus on next?”
Based on conversations with leaders across retail, housing and care, a few clear themes are emerging.
This is how exec teams are thinking about AI in 2026 and what they’re doing differently as a result.
1. Fewer ideas, more follow-through
One of the biggest shifts we’re seeing is restraint.
Instead of launching lots of new AI initiatives, execs are narrowing their focus. The question has changed from “what else could we try?” to:
- What already works?
- What delivered real value?
- What’s worth scaling properly?
In 2026, success will come from taking a small number of proven use cases and rolling them out consistently across teams, regions or functions; not from starting fresh every quarter.
2. AI is being planned like any other business capability
AI is no longer sitting off to the side as a separate programme.
Execs are building it into:
- Operating models
- Transformation roadmaps
- Workforce planning
- Data and technology strategies
That means clearer ownership, clearer expectations, and clearer measures of success.
In practical terms, this looks like:
- Named owners, not shared accountability
- Budget aligned to outcomes, not experimentation
- AI decisions being made alongside other strategic priorities, not after them
3. Readiness is now the main investment
In 2026, many exec teams are spending less time choosing tools and more time fixing what sits underneath them.
They’re asking:
- Can we actually access the data we need?
- Do teams trust the outputs?
- Do people know how to use AI in their day-to-day roles?
Data quality, access, integration and skills are where the real investment is going. Not because it’s exciting, but because without it, nothing scales.
4. Frontline teams are being brought in earlier
One of the clearest lessons from 2025 was this: AI only works when it fits how people actually work.
In 2026, execs are planning for:
- Earlier involvement from frontline teams
- More time spent validating outputs in real-world scenarios
- Clearer communication around what AI is (and isn’t) there to do
This shift is especially important in environments like retail and care, where confidence, consistency and trust matter more than clever features.
5. Governance is being treated as an enabler, not a blocker
Last year, governance was often seen as something that slowed AI down.
This year, execs are reframing it as what makes AI usable at scale.
That means:
- Clear rules around data use and ownership
- Agreed thresholds for risk and oversight
- Confidence that AI outputs can be relied on in decision-making
Done well, governance doesn’t limit progress; it removes uncertainty.
6. Success is being defined more simply
Finally, execs are getting more realistic about what “good” looks like.
In 2026, success isn’t:
- The most advanced AI
- The biggest transformation story
- The most impressive demo
It’s:
- Less manual work
- Faster, better decisions
- More headroom for teams
- Clear returns on effort and investment
Final thought
2026 won’t be the year of AI breakthroughs.
It will be the year of AI follow-through.
The organisations that get the most value won’t be the ones chasing the newest ideas. They’ll be the ones doing the basics well and sticking with them.
If you’re planning your AI priorities for 2026, the question isn’t “what’s possible?”
It’s:
“What are we actually ready to make work?”
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