Patrick Thompson already has a CIO Hall of Fame IT career in his back pocket, but now he’s bringing his well-honed insights and focus to this pressing issue: How CIOs must transform their approaches to succeed in the age of artificial intelligence (AI).
Inducted into CIO.com’s Hall of Fame in 2019, when he was with Albemarle Corporation, Thompson is now global senior vice president of Customer Transformation at Celonis, where he leads a team of customer transformation advisers, field CTOs, and enterprise modernization specialists to help Celonis customers get the full value from its platform. We sat down with Thompson to get his thoughts on what’s working (and what’s not) as CIOs try to transform their organization for the AI era.
Q: How is the CIO role changing with the rise of generative and agentic AI?
A: The CIO role has evolved into more of a business role than it ever has before. We used to always say, “Align with the business.” Then we said, “Enable the business.” Now we’re saying, “We are the business.” GenAI [generative AI] is on the priority list of every board member and every CEO. They are getting funding to do this, and you cannot do it without a good CIO.
Q: What can CIOs do to make sure their organization’s AI investments are creating business value?
A: Everybody thought AI was going to just work out of the box. But when you put it on top of data that is not ready for AI, you get a failed situation. That creates pressure. You just made these huge investments in AI, but you have nothing to show for it. If you’re going to invest in AI, it must have a return on investment [ROI]. You need to figure out where the pain is in the organization, where humans need the most help, and how to use AI to make people five or 10 times as efficient.
Q: How can CIOs move their organization from AI pilot projects — which, for many, have failed to show returns — to scalable enterprise solutions?
A: Once you find the business cases, you have to get the right infrastructure in place and the right contextual data to make AI successful. Otherwise, the technology will fail again, even though you identified a use case with a good ROI.
Q: How can CIOs apply lessons from earlier in their career to set their organization up for sustained AI success?
A: Good IT is good AI. If you have the right structure, staffing, and centers of excellence — if you have the right security, architectural review boards, and governance — those are fundamental. If you do those IT things well, that also applies to AI. AI is just another tool. It’s not some unicorn. The principles of good IT are what make AI successful.
Q: What steps can CIOs take over the next 12 months to ensure that AI investments lead to returns for the business?
A: Make sure you understand the power of contextualizing your data and your systems of record. That is going to 10x the speed and scalability of your AI strategy. There are a lot of ways to contextualize data, but many are very expensive and time-consuming, and they don’t evolve. When systems change, you need to be able to get back into the contextual layer to keep AI working. Contextualizing data is the most important thing you can do to make AI successful.
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