This transcript has been lightly edited for clarity.
How can COOs rewire their organizations to unlock enterprise-wide impact from AI investments?
A few years ago, one of my CXO clients said he sees AI everywhere except the bottom line. I think we are far beyond that now, thankfully. We moved from this notion of doing pilots to actually reimagining entire domains. And as you reimagine domains, think through the end-to-end workflow: How are you going to change that? Where are you going to use predictive insight from machine learning? How are you going to use gen AI to come in and drive more creative insights, more synthesis? And this is the year of agentic AI, where we are automating entire workflows.
As a COO, and as any other CXO, the critical thing is to prioritize high-value domains—and as you do this, adopt a factory mindset. We have implemented AI factories with some of our clients, where you build this for scale right from the get-go. You componentize code, you build product families, and you build code blocks so you can reuse them.
By doing that, you achieve better, faster, cheaper, with every single product going forward.
How can organizations cut through the noise to prioritize AI use cases that deliver measurable and scalable value?
The first stage of going through an AI transformation is to reimagine domains and prioritize domains by value. For example, a domain like exploration in the resources industry is very data-intensive, but it takes three to four years for the value to show. On the other hand, a domain like production optimization or manufacturing excellence—where you’re improving the yield, the energy efficiency, or the throughput of a process—you would find results very quickly, in eight to ten months. So, getting that right mix of domains where you get value quickly and where value realization comes in a bit later—phasing that is critical.
I think several of our clients have now realized there’s a lot that can be done with existing data systems and existing OT-IT infrastructure. Just using that purposefully unlocks a lot of value and creates energy in the organization toward AI.
Why is change management the make-or-break factor for scaling AI transformations?
Ultimately it comes down to use equals value. The front line needs to use AI solutions and get used to AI being a part of how they work. More than 80 percent of Lighthouses have clearly created mechanisms and have had purposeful capability building and change management programs to ensure that the front line adopts AI.
You need the senior leaders of the business to be AI sponsors, asking questions like “What if?” and “What’s the status?”
You need the top 100 leaders of the organization who actually lead critical functions or critical businesses to be AI champions, accountable for business delivery. Then you need the tech organization and the line organization to step up in terms of translation, as well as building domain-led AI talent.
