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AI has moved from being a futuristic idea to a key driver of business transformation, one which permeates most if not all functions of a thriving operation. As a result, companies are now asking themselves whether they need a Chief AI Officer (CAIO).
On a recent Deep Learning with PolyAI podcast episode, hosts Damien and Nikola (CEO and Co-Founder) talked about the rise of CAIOs, their roles, and how AI is shaping business operations. They also explored how AI-focused positions compare to traditional executive roles, why having a clear vision matters just as much as technical expertise, and what the future of AI leadership might look like in large organizations.
The rise of the CAIO
The rise of AI is similar to previous technology shifts, like the adoption of cloud computing. Just as companies created Chief Digital Officers (CDOs) to lead digital transitions and Chief Security Officers in industries where compliance and infosec are paramount, many are now appointing CAIOs to manage AI strategies. The challenge? AI isn’t just a tool; it’s changing the way businesses operate.
Nikola points out that a CAIO may start with a small, specialized team to experiment with AI without immediate pressure to deliver results. The long-term goal, however, is to integrate AI across the company and empower teams with AI-driven tools and processes.
Finding the right leader
The CAIO role requires a rare mix of skills. Damien highlights that while Chief Revenue Officers (CROs) often have established networks and proven strategies, experienced CAIOs are much harder to find. They need technical knowledge, strategic vision, and the ability to navigate company politics.
According to Nikola, effective CAIOs should be able to:
- Cut through AI hype to identify real opportunities.
- Lead cross-functional teams to implement AI.
- Secure resources and support to prioritize AI initiatives.
AI adoption: Fear and opportunity
AI’s potential to disrupt industries creates both excitement and fear. Companies that don’t adopt AI risk losing market share to competitors that do, and businesses need to decide whether AI will simply support their current processes or completely transform their operations.
For those choosing transformation, the CAIO—or a similar leader—becomes key to reshaping the company. But success depends on more than one hire. It requires buy-in from the entire executive team.
Competency centers: An alternative model?
Damien raises another possibility: Instead of a single CAIO, companies could create AI Competency Centers that become internal hubs dedicated to AI strategy, development, and governance. These centers could complement a CAIO or serve as an alternative model, focusing on upskilling employees and scaling AI adoption across departments.
For example, customer service agents might shift from handling routine calls to training AI systems and updating knowledge bases. This preserves jobs while increasing the impact of human expertise.
Skills for the AI era
What does it take to succeed in this AI-driven world? Nikola stresses the need for leaders who can:
- Separate AI hype from reality.
- Build strong technical teams.
- Rally internal support to make AI a priority.
The ideal AI leader is part strategist, part salesperson, and part technologist. They need to make the case for AI investments while ensuring those investments deliver real value.
Preparing for the future
Whether through a CAIO, an AI competency center, or another structure, businesses must take AI seriously. As Damien points out, you’re likely not going to lose your job to AI, but you could easily lose it to someone who’s experienced with AI systems.
The message is clear: Companies must build strong teams, adopt smart strategies, and prepare for an AI-driven future. For aspiring AI leaders, this means developing the technical, strategic, and persuasive skills needed to lead this transformation.
Watch the full episode about CAIOs and AI competency centers on our podcast ‘Deep Learning with PolyAI’ here.
