The AI skills gap is real. A recent study from Randstad, the recruitment company, found that job posts referencing generative AI skills have risen by 2,000% since March. It’s the third most sought-after skill set and one of the shortest in supply.
The logical step for enterprise companies is to appoint a chief AI officer (CAIO) to kickstart their efforts. Earlier this year, Dylan Fox penned an opinion piece arguing that every Fortune 500 business needs a CAIO.
“Companies that do not integrate AI into their product, operations, and business strategy will struggle to remain competitive — and fall behind those that do,” Fox wrote.
It’s a compelling argument that makes sense at the enterprise level. But what about everyone else? Startups and scale-ups need to integrate AI just as badly — especially if they’re trying to fundraise in this AI moment. However, they often don’t have the resources or the organizational structure to support a senior executive focused exclusively on AI.
This is where a fractional AI officer comes in. Fractional leadership is a recent workforce trend: seasoned executives with subject matter expertise working across two or more clients simultaneously, lending their talents to rapidly growing companies that need their specific skill set but can’t afford it full-time.
Here’s the kicker: Having a fractional AI officer is superior to hiring full-time in one crucial respect. AI — especially generative AI — is such a new technology that breadth of experience across multiple companies gives fractional executives an edge over their full-time counterparts.
The three stages of AI adoption
While the promise of generative AI is significant, it’s hard for companies to establish a reliable ROI metric early in the adoption curve, especially in an environment where companies are expected to be more conservative in spending.
Increasing productivity and workflow efficiency will likely be the No. 1 driver for generative AI adoption.
Horizon 1: Workflow efficiency + productivity
Due to the market challenges, companies are looking for ways to free up cash and lower spending to keep budgets flat in 2024. That’s why increasing productivity and workflow efficiency will likely be the No. 1 driver for generative AI adoption. A recent BCG study found that generative AI can drive significant improvements in workflows, operations, and internal tooling — participants who used GPT-4 completed 12% more tasks on average and 25% quicker than the control group without GPT-4. This is where we will see ROI first. Let’s call that Horizon 1.
Horizon 2: Customer experience
This is a great steppingstone into the next stage of generative AI adoption: improving customer experience. These days, customers expect drastically better — and more personalized — digital experiences. They’ll switch to your competitor if you don’t remember who they are or anticipate their needs. Generative AI can bring personalization to your digital experiences.
Horizon 3: Product innovation
A fractional AI executive can help implement freshly established best practices to integrate generative AI “superpowers” into legacy flows and core internal capabilities. That will improve efficiency, reduce cost, and create momentum for the more advanced AI projects that will pay for themselves. Those projects represent Horizon 3, the frontier of innovation, where new products create new revenue streams.
Building profitable products with generative AI is a significant challenge that many startups focus on full-time and still need help with. This will be even more challenging if your company isn’t an AI-first company. A fractional AI officer’s primary role is to ensure your AI initiatives get the kind of leadership and cross-functional attention they need.
The mistake companies make is giving the problem to IT and telling their CTO to develop AI. Instead of generating tangible value for the business, it wastes time playing around with fancy new technology just for the sake of it.
The fractional AI officer edge
Piers Linney, a fractional AI officer in the U.K., said, “Fractional CAIOs provide an outsider’s objectivity. Their cross-industry experience also fuels novel ideas and best practice sharing not hampered by internal politics, pressures, or short-term priorities.”
It works for the executive because they need the 24/7 pressure of a traditional leadership position. They work with exciting young companies and have a more significant impact than they would at a public behemoth. It works for companies as an alternative to expensive and finite consulting services: A fractional AI officer becomes a member of your leadership team, managing direct reports and owning outcomes.
Without a dedicated AI executive, the responsibility for implementation in an SME falls to the CTO, who has to take time away from all their other responsibilities to do an ad hoc crash course on this new technology. Moreover, the ability to analyze risks and help refine strategy from the top down is essential in the nascent stage of a transformative new theory.
Here’s what a fractional AI officer offers that other solutions don’t:
- Diversity of experience: The nonstop development of new tools, the publication of recent papers, and the all-around zaniness of the current AI landscape necessitate a different approach. Fractional CAIOs, by working with multiple clients across varied industries, have a greater diversity of experience than those who stay in-house. This affair allows them to tailor strategies to each organization’s unique needs. That intangible outsider’s knowledge fuels innovation and helps guard against the unknown, especially around risk and compliance.
- Dedicated expertise without undue cost: The prospect of hiring a full-time CAIO is impractical for startups and scale-ups operating on lean budgets. Fractional CAIOs are a cost-effective alternative, offering specialized expertise without the financial strain of a permanent executive position. This model allows companies to access top-tier talent and insights on a need-based framework, ensuring that resources are utilized efficiently. The agility and flexibility afforded by fractional CAIOs enable organizations to adapt swiftly to market changes.
- Relentlessly pursuing the business case: If you drop all generative AI responsibility on your IT department without a deep integration into core operations, the scale of adoption will be limited. Generative AI projects, for their own sake, typically lead nowhere — they need a business case. The most useful generative AI investments are those built with cross-functional teams dialed in on either workflows or customer experience.
At A.Team, we’ve seen firsthand the impact fractional AI officers can have. Tomislav Peharda joined Growth Warrior Capital, a venture capital fund supporting female and diverse founders, as a fractional AI officer, where he architected a generative AI tool to help portfolio companies craft custom pitch decks and raise money.
With a crack product team, Peharda built the platform’s backbone, refined its intelligence, and sculpted its user experience to democratize startup fundraising with an AI-powered platform.
Ready or not, this is happening
Among the Fortune 1000, 84% of companies plan to increase their data, analytics, and AI investments next year.
“Now is the time to establish data governance and cybersecurity measures to use these new capabilities responsibly,” said Philippe Rambach, CAIO at Schneider Electric, a global energy management company.
Part of the solution is shifting to what the authors call an “ecosystem mindset.” As Rambach explained, “The new nature of competition is really not about technology; AI technology moves too fast for that. It’s about the value you deliver to customers. And whatever value you deliver, it can be augmented through partnerships.”
A fractional AI officer is a luxury for startups trying to conserve cash. But for many, it’s an investment they can’t afford not to make.