Who’s leading your AI strategy? If you’re like the average company, the answer may be no one. Yet, according to Gartner, 91% of organizations with high AI maturity have already appointed Chief AI Officers (CAIOs) or other AI leaders.
These dedicated experts help companies go from experimenting in silos to executing at scale, ensuring every investment drives measurable results. Without their strategic guidance and ownership, even the best tools can fall short of expectations.
But not every organization needs, or can justify, a full-time executive hire. To decide what’s right for the business, leaders must understand what CAIOs do, when they’re needed most, and why growing companies often opt for the fractional model.
How CAIOs Turn AI into ROI | Attend Webinar
What a CAIO Actually Does
A Chief AI Officer is responsible for overseeing an organization’s AI strategy, governance, and implementation. Unlike technical leads who focus solely on the development of tools or models, CAIOs operate at the intersection of business goals, data, technology, and people.
Their mandate is simple in essence, but not easily achieved: ensure every AI investment aligns with strategic objectives and delivers measurable value. In practice, CAIOs empower organizations to:
- Define company-wide AI strategy and roadmaps
- Prioritize AI use cases and investment portfolios
- Establish AI governance, risk, and responsible-use standards
- Scale AI initiatives from pilots to production
- Align AI efforts across teams, functions, and leadership
- Upskill teams through AI workshops and training programs
- Measure AI performance, ROI, and business impact
- Advise executives and boards on AI direction and decisions
Today, more than 1 in 4 companies now have CAIOs, and 66% of those CAIOs expect most companies to hire for the position within two years. For large enterprises, this often means filling a full-time executive role. For many growing organizations, it doesn’t have to.
How Fractional CAIOs Work
77% of business leaders report that AI is increasing their need for specialized, fractional talent over traditional full-time roles. The fractional model allows you to access C-level expertise without the long-term commitment or cost of a full-time hire.
Unlike permanent and interim leaders, these part-time executives often work with multiple clients in tandem, devoting different hours to different projects and initiatives. However, they can provide both high-level guidance and hands-on management.
These leaders also embed themselves within your organization, balancing fresh perspectives with an in-depth understanding of your strategic objectives. This allows them to quickly diagnose challenges, implement effective strategies, and upskill in-house teams.
In addition, they help deliver accelerated growth and improved performance in shorter timeframes by focusing exclusively on AI efforts, as opposed to dividing their attention across broader digital transformation initiatives.
When to Hire a Fractional CAIO
Many organizations reach an AI inflection point long before a full-time executive hire makes sense. That point comes when you decide, receive budget for, or begin to invest in AI, but your executive team lacks the time or knowledge necessary to deliver.
These are some of the most common indicators that a company is in need of AI leadership.
- AI’s value is clear. Next steps are not. The opportunity is obvious, but what to prioritize, build, and scale is unclear.
- Experimentation is up. Strategy is not. Teams are testing use cases without a clear roadmap forward.
- AI is everywhere. Results are not. You’re using AI tools, but they’re not translating into measurable impact.
- Success exists. Progress does not. Early wins exist, but nothing is operationalized or expanded.
- AI leadership is needed. New hires are not. Executive-level AI expertise is required, but a full-time hire isn’t justified.
Why Hire a Fractional CAIO
Over 95% of AI investments fail to yield significant returns. Only 33% of companies have moved beyond AI pilot experimentation. And many struggle to even get started.
Common challenges include unrealistic expectations, unclear objectives, and inefficient integration. Studies show the difference between the winners and laggards often lies in AI leadership. And few existing leadership teams have the expertise or bandwidth to lead AI efforts on top of their primary responsibilities.
CAIOs often bring decades of relevant expertise to make AI adoption manageable and scalable, driving up to 36% higher ROI. Guiding teams across functions, these leaders oversee, accelerate and elevate the following and more:
- AI Roadmapping
- AI Use Case Prioritization
- AI Governance and Oversight
- AI Workflow Design
- AI Engineering
- AI Automation
- AI Agent Orchestration
Final Thoughts
Many companies have lived through a version of the same story. An AI budget is approved. A vendor delivers a compelling demo. A pilot launches. Six months later, it has stalled, consuming budget, eroding confidence, and producing no measurable change to how the business works. Others never get that far.
BCG’s 10-20-70 principle reveals what needs to go right that often goes wrong. AI success is 10% algorithms, 20% data and technology, and 70% people, processes, and cultural transformation.
The challenge is that most organizations have invested heavily in the 10% and almost nothing in the 70%. What they’re missing isn’t a better model. It’s a leader. And today’s companies don’t need to invest in a full-time hire to access an experienced AI executive.
About Our AI Solutions
Onward Search empowers companies to hire AI-fluent professionals, upskill their people, and make AI transformation possible. Recognizing a need across clients, we built a network of AI executives who can help you build a roadmap, move beyond experiments, and deliver measurable impact.
Example CAIOs
Frank has led $30M AI transformations.
With 30+ years of experience, Frank has co-led multiple $30M+ AI transformations, architecting AI strategies impacting 130K+ employees, and delivering measurable ROI for companies across industries.
Jigyassa led AI efforts at Uber, Meta & X.
Featured across 200+ media platforms, Jigyassa is a 12-time award-winning AI leader with a proven ability to build and scale revenue-critical ML systems across complex organizations. She has previously led AI efforts at Uber, Meta, and Twitter/X.
Request a CAIO
Fill out the following form, and a member of our team will be in touch within 24 hours.
