What lies ahead for enterprise AI strategies in 2026?

After a year dominated by the race to build ever larger, all-purpose AI agents, many organisations are realising that scale alone is not a measure of value.

Andy MacMillan, CEO at Alteryx, believes 2026 will usher in an era of “automation with purpose”, where businesses prioritise domain-specific AI applications that integrate seamlessly into existing workflows rather than ambitious but isolated initiatives.

Here, Andy explores how this transition will reshape enterprise ownership, inform AI strategy and redefine the role of data leadership in an era of more pragmatic AI.

How do you anticipate enterprise AI rollout strategies to evolve in 2026?

2025’s push to build massive, all-knowing AI agents capable of handling a wide sweeping set of enterprise tasks hasn’t worked. That’s why I anticipate those projects slowing down in 2026. 

Instead, we’ll see a renewed focus on automation with purpose. In practice, this means more domain-specific AI use cases and AI agents. 

The end goal here is to embed AI capabilities into existing, proven workflows versus building all-knowing bots and I think that’s a better route to success.

How would that change influence ownership of AI strategy and implementation in enterprises?

I think we’ll see something of a course correction. IT teams have taken the lion’s share of AI budgets over the past few years but the shift towards domain-specific integration of AI into proven workflows will see line-of-business leaders command a much bigger share of budgets. 

They can identify real problems for AI to solve quicker than IT teams and I think that’s going to be acknowledged much more widely with those leaders being handed greater responsibility for AI strategy and implementation.

How does this vision align with efforts to centralise AI strategy and rollout?

I actually see the momentum moving away from centralisation. I see a growing realisation that the dissemination of AI into businesses has to be led by line-of-business leaders versus a central strategy overseen by IT. 

This is why I’m expecting more CEOs in 2026 to empower CFOs, sales leaders and other business leaders to find and fund AI solutions that directly advance their goals.

What are your thoughts on the relevance of the Chief Data and Analytics Officer (CDAO) role in 2026 as AI continues to transform how enterprises work with data?

For continued relevance in the new year, I’d advise CDAOs to be more pragmatic, learning to work and empower the business from the data infrastructure they have.

For too long, analytics leaders have insisted that data isn’t organised enough to generate insights. But perfect data rarely exists. 

The leaders who will win in 2026 will be the ones who can deliver impact now, even without a single, perfectly organised system. 

The mandate is shifting from ‘organise everything first’ to ‘solve problems now’.