Feature
Figuring out how to manage AI and keep up with the latest developments and lawmaking can be a headache. But do you really need a Chief AI Officer (CAIO)?
Companies rushing to appoint a CAIO remind me of governments creating “czar” positions to handle big, tricky problems. History shows these figureheads don't always have the power to make the important changes we hope for. We’ve had multiple drug, energy and cybersecurity czars, for example, yet issues persist in all of these areas.
I worry the same could happen with CAIOs; they could become the symbol of AI strategy but without any real power or accountability to make a difference. Putting all our AI hopes and dreams on one person's shoulders simply isn’t the best strategy — at least not now.
Why a Chief AI Officer Model Fails
The smart folks at Gartner agree with me, at least somewhat. While they believe AI needs a dedicated owner, they say it shouldn’t rise to the level of a C-Suite title.
According to their research, a majority of the accountability today falls onto CTOs and CIOs, with about 16% of organizations depending on distinct heads of AI or chief digital and artificial intelligence officers (CDAO).
Having a CAIO (or similarly isolated AI-centric role) can backfire. You'd think it would make a company better at using AI, but it can actually create an "AI island" isolated from the rest of the business. This is unproductive because the whole point of AI is to improve how things already work. If the AI team doesn't deeply understand what the other teams need, it could build solutions that don't really help. CTOs and CIOs, already embedded in the business and meeting the needs of employees, can drive a more integrated strategy.
Putting all the AI pressure on just one person also isn’t realistic. If things go wrong, it's easy to hide mistakes and not learn from them. Or, a CAIO might get excited about flashy AI projects that sound cool but don't actually match the company's goals. Having an AI skunkworks may sound logical and warranted, but it can actually make it more difficult to learn and evolve quickly.
Keeping AI separate also slows down organizations from making AI a natural part of the company's work, which means lost time and missed opportunities. People in other departments might not even understand what AI can do, so they likely won't be on board with using it. Plus, if no one shares what works and what doesn't, the company can't get smarter about using AI as a whole.
Related Article: The Impact of AI on the Future of Work: Embracing the Power of Collaboration
AI Is a Team Game
To make AI work, the whole company needs to be involved. Each department, from IT to sales to top leadership, should have a say in (and responsibility for) how AI is used. This ensures that the AI tools that get built or bought actually match the company's goals and help people get their jobs done. Everyone needs to be on the same page about what AI can and can't do, so we can make smart decisions about its role.
Well-understood rules for using AI are also important. A clear plan on how the company will use AI fairly, how data will be kept private, and who will make the final call on AI projects is a must. This will keep things honest and everyone accountable, and it will ensure all are complying with existing rules and regulations.
Everyone within the organization also needs to understand the basics of AI. Knowing the potential and limitations of AI enables people at all levels of the company to come up with ideas for how to best leverage it. This gets people excited and ensures AI is used in a smart and ethical way. Investing in teaching everyone about AI creates an environment where everyone has the ability to tap into the technology and help the team get ahead in the long run.
When a CAIO Might Make Sense
There are times when having a CAIO makes sense. If your company's focus is embedded in AI innovations, then yes, a dedicated leader is a must. That person would oversee cutting-edge research, ensure everyone is aligned toward the same goals and figure out how to bring all the moving parts together.
Also, if your company is already well versed in AI and is using it to leapfrog the competition, a CAIO could possibly drive widespread, consistent adoption. A CAIO then becomes like the conductor of an orchestra, making sure everyone has what they need, teams are sharing what works, and new AI projects get rolled out smoothly everywhere.
The number of companies that meet those conditions is few and far between, though. And even in those organizations, a CAIO isn’t the end all, be all of success.
Related Article: AWS's Diya Wynn: Embed Responsible AI Into How We Work
Webinar
Sep
25
CMS Briefing: A Live Look at What’s Next in AI-Driven Platforms
Learn how leading organizations are using AI‑driven tools to publish faster, personalize smarter and stay secure.
Register
Webinar
On demand
Ready or Not: How Data-First Organizations Are Unlocking Agentforce Potential
Learn how to cut through the noise, activate Agentforce and build a Salesforce AI strategy that actually delivers.
Watch Now
Webinar
On demand
AI in Customer Service: Faster Resolutions, Happier Customers
Don’t let rising demand burn out your team. See how to build a smarter, more resilient support org.
Watch Now
Webinar
On demand
From Hype to High-Impact CX Strategies That Actually Scale
Turn buzzworthy AI and outsourcing trends into measurable CX wins with fresh 2025 data.
Watch Now
Webinar
On demand
Insights to Action Rethinking the Contact Center for Real Business Impact
Join our exclusive webinar to hear CX executives share their innovative strategies for transforming service delivery.
Watch Now
Webinar
On demand
Accelerating Healthcare Ops with AI
Sign up to see how your peers are putting AI to work — and making it stick.
Watch Now
AI Is for All
Don't think of AI responsibility as one super-smart AI person who can wave a wand and fix all of your challenges. Trying to force AI from the top down usually ends up being an ineffective solution for a complex problem. And borrowing from a czar model with a nice title but isolated work doesn’t help anyone.
Instead, we need to embrace AI as a new tool that everyone in the organization has an opportunity to explore. It needs to fit in with the work that’s already being done, have clear goals and outcomes, and be everyone’s responsibility to make it work.
A CAIO doesn’t relieve organizations of helping people learn the basics of AI, either. The real power of AI isn't just having a dedicated job title. It's the whole company working together to find better ways of doing things and solving problems we already know we have.
