What is the role of a fractional Chief AI Officer?
In June I attended the AI Summit in London, and one of the topics that came up was the rise of a new executive role - the Chief AI Officer or CAIO.
In this article I’ll introduce the role of the CAIO, how it differentiates itself from that of a CIO or CTO, and why for many companies, exploring a fractional CAIO can give you more benefit than hiring for a full time internal role.
What is a Chief AI Officer?
AI is moving beyond the hype and into real-world business value. While there are only a small number of business use cases in production, the pace of innovation in the models is advancing so fast companies are skating to where the puck will be in 2-3 year’s time, and that is with AI as a key enabler of most business processes.
But AI is a new and complex topic.
It introduces many new technology vendors, from models, to vector databases, to data sources.
It creates the need for an organisation-wide change programs.
It disrupts how businesses think about the products and services they offer to their customers.
It challenges the company’s people strategy by potentially displacing many roles currently delivered by humans.
The Chief AI Officer leads this strategy, as a peer to the CEO, as they redefine what a company looks like in an AI future:
Developing and implementing AI strategies aligned with business goals
Identifying AI opportunities across different departments
Overseeing AI project selection, prioritisation, and execution
Ensuring ethical AI practices and addressing potential biases
Staying current with AI trends and emerging technologies
Partnering with and learning from leading vendors across the AI ecosystem
Developing a composable AI orchestration framework
Fostering a data-driven culture within the organisation
Managing AI-related governance, risks and compliance issues
Collaborating with other C-suite executives to integrate AI into overall business strategy
I think of an octopus - the CAIO sits at the top leading the control tower, whilst also driving the AI strategy into the tentacles of the business through change programs, incentives and ongoing support.
Why not the CIO or CTO‘s responsibility?
The CIO is typically focused on a company’s internal systems, while the CTO is typically focused on external digital products and services for customers, suppliers and partners.
Neither of these has a heritage and deep experience in the new architecture and tools required for building an AI strategy.
They may well have data, machine learning and GenAI engineers in their teams.
They may well have developed AI proofs of concept.
But they don’t have the broad expertise around developing an AI strategy that is embedded into the business units themselves or the deep relationships with the new breed of vendors that make up the AI stack.
The risk is that AI becomes an IT project, just another tool that IT understands but is not embedded into every team, process and person in the company.
The rise of the fractional CAIO
Before we get into more detail about the role of the CAIO, I want to touch on why the role of the fractional CAIO is gathering pace as a delivery model for this expertise.
Skill shortage - there are very few senior executives who have AI experience, partnerships and processes. For even mid-to-large companies with a budget, finding talent is challenging.
Cost effectiveness - for companies that are still finding their feet with their AI strategy, a full time role may not make sense.
Diverse experience - this is the most important reason to look at fractional resource. The AI world is moving so fast and changing so rapidly, that being able to see what others are doing is the key to inspiring your own use cases.
A full-time internal role very quickly starts to look inward and loses that experience of other industries and functions.
I’m a great fan of David Epstein’s book ‘Range’, which makes the case for generalist experience. That is very much the case here - what a CEO wants from their CAIO is insight into how other companies are transforming with this technology.
The CAIO’s team
The CAIO may have a team around them, or they may be dotted line into roles in the CIO, CTO or Chief Data Officer’s team - especially if the CAIO is fractional.
Key roles that you’d expect to see:
Data scientists
Machine learning engineers
Data engineers
Integration architects
Business Analysts
Change Managers and trainers
Project Managers
The change team is a key element - AI strategy is a people change strategy more than a technical change strategy - the CAIO will be closely aligned with HR to develop training programs and recruitment strategies for AI talent.
A partner to the business
One of the main reasons for having the CAIO as a separate role from the CIO or CTO is that the most impactful AI use cases come from the business units themselves.
The business understands their end to end process. They understand the nuances, the blockers, the workarounds and the opportunities that AI could have to deliver a better customer and employee experience.
Go back to the octopus - the CAIO must build skills and relationships into every tentacle!
The CAIO must figure out how to embed AI skills and ambition into every single team - AI is not an IT initiative. Instead of taking AI to the problem, you succeed by taking the problem to AI.
Key partners for the CAIO
That said, the CAIO can’t work in a vacuum on a special ops mission - they need to maintain close relationships with other senior leaders:
CEO: Aligning AI initiatives with overall business strategy
CTO/CIO: Integrating AI solutions with existing IT infrastructure
CFO: Budgeting for AI initiatives and measuring ROI
CDO (Chief Data Officer): Ensuring data quality and availability for AI projects
COO: Implementing AI solutions to optimize operations
CRO/CMO: Leveraging AI for marketing and customer experience improvements
CHRO: Addressing the human impact of AI adoption and workforce planning
What’s the ROI on an AI strategy?
At the AI Summit in June the incoming CTO of PwC UK said that whenever he is asked about the ROI of their investments in AI he responded,
“The ROI is our right to compete in three years time”
In the short term it can be difficult to say how the investments in change, in technology, in hiring have an impact - but we know that if we do not embed these skills and behaviours in our businesses now, it will be too late to start.
That said, there are some metrics that the CAIO can start to model and report on:
ROI on AI investments (hard to measure in the short term)
Number of successful AI project implementations to production
Improvements in efficiency and cost savings attributed to AI
Revenue generated from AI-driven products or services
Reduction in errors or risks through AI-powered solutions
Increase in data-driven decision-making across the organisation
Employee adoption and satisfaction with AI tools
External recognition (e.g., industry awards, media coverage) for AI initiatives
I have highlighted three that get to the heart of why Executives are investing in AI (or any product or service):
Save money
Make more money
Reduce or mitigate risk
As a CAIO if you can tie your AI use cases to one or more of these you’ll be on the road to demonstrating the return.
Fractional CAIOs can bring a fresh perspective
As you start to consider who will be the senior leader for your AI strategy consider these questions:
Should we use an existing role (CIO/CTO/CDO) or create a new one?
How will we ensure we bring a fresh perspective with fresh insights that in-house executives may miss?
Is this a business strategy role or a pure technical role?
Who would this role need in their direct or dotted line team?
How do we embed this role into every part of the business and avoid a figurehead with no power?
How are you approaching AI strategy in your own organisation?