Main image of article The Chief AI Officer: What Is It and Who Needs One?

Summary

With artificial intelligence (AI) becoming a critical element in digital transformation efforts, a new C-suite role is taking hold: the Chief AI Officer (CAIO).

More than just your standard-issue senior executive, the CAIO is tasked with embedding AI across every function of the enterprise—from product development and operations to HR, finance, and marketing.

Unlike CIOs or CTOs, whose focus is typically on infrastructure or engineering, the CAIO is responsible for turning AI into a strategic business driver. That means aligning emerging technologies with corporate objectives, managing complex risks like data privacy and model bias, and leading cultural change at scale.

For companies serious about AI, this isn’t a future role—it’s a present necessity. But it’s also one that demands broad authority, deep expertise, and a clear mandate from the top.

According to Benevity CAIO Ian Goldsmith, the role’s focus is fundamentally different from that of a CIO or CTO.

“The role of the CAIO is AI-first and business-outcome-focused,” Goldsmith says. “In contrast, the CIO is primarily infrastructure- and operations-focused, while the CTO is product- and architecture-focused.”

That distinction matters, especially as AI becomes central to both operational strategy and product differentiation. A CAIO isn’t just a technical expert; they’re a cross-functional leader who ensures that AI is not simply bolted onto business processes but embedded strategically across the organization.

Joe Mayberry, head of AI at SailPoint, echoes that sentiment, highlighting the CAIO’s responsibility to unify AI adoption across all business functions. “I view the primary difference as the CAIO is responsible for corporate AI strategy and execution across all major corporate functions of the company, not just internal AI tools or external AI products and services,” he explains.

This includes working with HR on organizational change, collaborating with finance to rethink capital allocation in an AI-first model, and aligning marketing with evolving AI branding narratives. “The CAIO must ensure total corporate alignment to the unified adoption of AI technologies across all functions of the organization,” Mayberry adds.

CAIOs don’t just implement AI—they shape the strategic direction of the company in response to AI’s rapid evolution.

Mayberry believes the role includes a responsibility to influence high-level decisions: “It is job zero of the CAIO to make the current corporate strategy successful, and where necessary, considering their knowledge of how AI is changing the company’s market, advocate for tweaking the corporate strategy.”

That strategic influence requires deep awareness of technological trends, market signals, and internal constraints. “Ensuring the culture change and execution rate matches that of the company they serve is critical,” Mayberry adds.

That means a successful CAIO must recognize when rapid change is feasible and when deliberate pacing is wiser.

Goldsmith says he sees the CAIO as a business partner and a product strategist. At Benevity, for example, he’s focused on embedding AI across both the company’s product platform and internal operations. “AI is core to our business strategy,” he says. “I play an integral role in ensuring we are leading that transformation in the corporate social responsibility and social impact software industry.”

The CAIO role demands a specific combination of traits as a cross-functional influencer whose ideal background combines technical AI expertise, strategic leadership, and broad business acumen.

“They should also serve as an evangelist for AI, both externally and internally,” Goldsmith explains.

Mayberry largely agrees, but puts even greater emphasis on business leadership: “I do not view the CAIO position as a purely engineering, purely product, or purely managerial position.”

Instead, the ideal CAIO is someone with a general management background who’s deeply engaged with AI technologies and understands the nuance of deploying them in dynamic environments. While selecting the best technologies, aligning the organization, or executing rapid product development cycles are all important, none alone are sufficient.

Soft skills—especially around change management and cultural leadership—are also critical.

Both leaders suggest the CAIO is often most effective when they lead through influence and principle-based decision-making rather than direct control.

Managing risk is a major part of the CAIO’s mandate. That includes bias, compliance, privacy, and model transparency.

Goldsmith outlines a comprehensive approach, which begins with creating company-wide AI ethics and responsible use guidelines. It also includes monitoring and adapting to changing data privacy laws and regulations. He emphasizes the need for AI governance frameworks, cross-functional oversight, and close collaboration with legal and cybersecurity teams.

Mayberry adds that effective risk management also depends on judgment under uncertainty. “There is risk in the unknown,” he says. “Having someone who is able to take limited information and place informed bets is critical.”

He also points to the value of experience in regulated or emerging technology sectors, such as healthcare AI or computer vision, as a predictor of a CAIO’s ability to navigate legal and ethical minefields.

To succeed, a CAIO must be a catalyst for AI adoption across the organization—not just a technical leader, but also a cultural one.

Goldsmith sees this as a two-pronged effort: an evangelist and champion for innovation and the use of AI, both in the products their company offers and internally across the organization.

That means embedding intelligent systems in both external platforms and internal workflows so that AI becomes a lever for both product innovation and operational efficiency.

Mayberry views the role as the cornerstone of corporate transformation, working alongside senior leadership to define function-by-function objectives that align with a unified AI strategy.

Measuring ROI on AI is tricky but essential, with Goldsmith and Mayberry both warning against focusing too narrowly on cost savings.

“To measure AI simply on a cost savings basis would be to completely miss the second half of the equation for ROI,” Mayberry says. “The first is an efficiency metric, the second is a product value accretion metric.”

Only by combining both can organizations understand the full return of their AI investments. For Goldsmith, the ultimate measure is alignment with purpose and business performance. “We are committed to creating new, measurable ways of doing good that also support strong business results,” he says. “Success also means helping organizations connect their business goals to purpose outcomes.”

Not every company needs a CAIO—yet. But as AI moves from isolated use cases to strategic imperatives, more organizations are asking whether their current leadership structure can keep up.

If AI is core to your business model, touches multiple departments, or requires cultural transformation to succeed, a CAIO may be essential. But the role must be empowered to drive change.

Ultimately, the CAIO isn’t just another tech executive, but rather a bridge between emerging technology and enterprise strategy, charged with guiding organizations through a once-in-a-generation transformation.

“Soft and expert power alone will not deliver the change at speed that is required to capitalize on the AI evolution,” Mayberry says. “The CAIO must have legitimate power—budgetary or direct management—to be effective.”

Interested in laddering your career into a CAIO position? Here’s a checklist of things to keep in mind:

  • Understand the Core Mandate: Recognize that the CAIO role is fundamentally about making AI a strategic business driver, not just implementing technical solutions. Your primary focus will be aligning AI initiatives with overarching corporate objectives.
     
  • Differentiate Yourself from the CIO/CTO: Clearly grasp the distinction. While CIOs focus on infrastructure and operations, and CTOs on product and architecture, the CAIO is AI-first and business-outcome-focused, embedding AI across all functions.

  • Embrace Cross-Functional Leadership: Prepare to work collaboratively across the entire organization. This includes HR (organizational change), finance (capital allocation), marketing (branding), product development, and operations. Unifying AI adoption is a key responsibility.

  • Develop Strategic Influence: Cultivate the ability to shape the company's strategic direction based on your understanding of AI's evolving impact. Be prepared to advocate for adjustments to the corporate strategy when AI presents new opportunities or necessitates changes.

  • Stay Abreast of Technological and Market Trends: Maintain a deep awareness of the latest advancements in AI, emerging market signals, and internal organizational constraints to inform your strategic recommendations.

  • Balance Speed and Deliberation: Recognize when rapid AI implementation is feasible and beneficial, and when a more measured and deliberate pace of change is necessary for successful adoption.

  • Become a Business Partner and Product Strategist: View yourself as an integral partner to the business, understanding how AI can enhance both internal operations and external product offerings.

  • Cultivate a Blend of Technical, Strategic, and Evangelistic Skills: While deep technical AI expertise is foundational, strategic thinking and the ability to evangelize AI's potential both internally and externally are equally crucial.

  • Prioritize General Management Acumen: Recognize that the CAIO role isn't purely technical. A strong general management background with a deep engagement in AI technologies is highly valuable.

  • Hone Soft Skills: Develop strong change management and cultural leadership abilities. The CAIO often leads through influence and principle-based decision-making rather than direct authority.

  • Champion Responsible AI: Take ownership of managing AI-related risks, including bias, compliance, privacy, and model transparency. Establish company-wide AI ethics and responsible use guidelines.

  • Implement AI Governance Frameworks: Develop and oversee AI governance structures, ensuring cross-functional oversight and close collaboration with legal and cybersecurity teams.

  • Exercise Judgment Under Uncertainty: Be prepared to make informed decisions with limited information, as AI often involves navigating the unknown. Experience in regulated or emerging tech sectors can be beneficial here.

  • Drive Adoption from the Inside Out: Act as a catalyst for AI adoption across all levels and departments. Embed intelligent systems in both customer-facing products and internal workflows to boost innovation and efficiency.

  • Collaborate on Function-Specific Objectives: Work closely with senior leadership to define AI-aligned objectives for each functional area of the organization.

  • Measure Success Beyond Cost Savings: Understand that the ROI of AI extends beyond efficiency metrics to include product value accretion. Focus on how AI contributes to both operational improvements and the creation of new value.

  • Align AI Initiatives with Purpose and Business Performance: Strive to connect AI implementation with the organization's broader purpose and demonstrate its contribution to strong business results.

  • Assess Organizational Readiness: Understand that the need for a CAIO typically arises when AI becomes central to the business model, impacts multiple departments, and necessitates significant cultural transformation.

  • Seek Legitimate Power and Authority: Recognize that to be effective, a CAIO needs more than just expert power; budgetary control or direct management responsibilities are often necessary to drive meaningful change.

  • Bridge the Gap Between Technology and Strategy: Position yourself as the crucial link between rapidly evolving AI technologies and the overall enterprise strategy, guiding the organization through a significant transformation.