AI skills the gap is real. A recent study by Randstad, the recruiting firm, found that jobs referencing generative AI skills have increased 2,000% since March. It is the third most sought-after skill set and one of the least available.
The logical step for companies is to appoint a Chief AI Officer (CAIO) to drive their efforts. Earlier this year, Dylan Fox wrote an op-ed arguing that every Fortune 500 company needs a CAIO.
“Companies that do not integrate AI into their products, operations, and business strategies will struggle to remain competitive and will fall behind those that do,” Fox wrote.
It’s a compelling argument that makes business sense. But what about everyone else? Startups and scale-ups need to integrate AI just as urgently, especially if they are trying to raise funds in this time of AI. However, they often do not have the resources or organizational structure to support a senior executive focused exclusively on AI.
This is where a fractional AI officer comes into play. Fractional leadership is a recent trend in the workforce: seasoned executives with subject matter expertise working for two or more clients simultaneously, lending their talents to rapidly growing companies that need their specific skill set but can’t afford it. It’s full time.
Here’s the kicker: having a fractional AI officer is superior to hiring them full-time in one crucial respect. AI, especially generative AI, is such a new technology that extensive experience across multiple companies gives fractional executives an advantage over their full-time counterparts.
The three stages of AI adoption
While the promise of generative AI is significant, it is difficult 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 number one driver for adoption of generative AI.
Horizon 1: Workflow efficiency + productivity
Due to market challenges, companies are looking for ways to free up cash and reduce spending to keep budgets stable in 2024. That’s why increasing productivity and workflow efficiency will likely be the main driver for the adoption of Generative AI. A recent BCG study found that generative AI can drive significant improvements to internal workflows, operations, and tools: Participants using GPT-4 completed 12% more tasks on average and 25% faster than the control group without GPT-4. This is where we will first look at ROI. Let’s call that Horizon 1.
Horizon 2: Customer Experience
This is a big step towards the next stage of generative AI adoption: improving the customer experience. Today, customers expect dramatically better, more personalized digital experiences. They will 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.