AI skills the void is real. A recent study by Randstad, the recruiting firm, found that jobs listing genetic AI skills have increased by 2,000% since March. It is 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 (CAIO) to jump-start their efforts. Earlier this year, Dylan Fox wrote one opinion piece arguing that every Fortune 500 business needs a CAIO.
“Companies that don’t integrate AI into their product, operations and business strategy will struggle to stay competitive — and fall behind those that do,” Fox wrote.
It’s a compelling argument that makes business sense. But what about everyone else? Startups and scaling companies need to incorporate AI just as badly — especially if they’re trying to raise funds right now. However, they often lack the resources or organizational structure to support a senior executive focused solely on AI.
Here comes a fractional AI officer. Fractional leadership is a recent workforce trend: experienced executives with subject matter expertise who work on two or more clients simultaneously, lending their talents to fast-growing companies that need their particular skill set but can’t afford to be full-time .
Here’s the gist: Having a fractional AI officer is superior to hiring full-time in one critical way. AI — especially genetic AI — is such a new technology that the breadth of experience at multiple companies gives part-time executives an advantage over their full-time counterparts.
The three stages of AI adoption
While the promise of genetic 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 No. 1 driver for AI adoption.
Horizon 1: Workflow efficiency + productivity
Due to market challenges, companies are looking for ways to free up cash and reduce spending to keep budgets steady in 2024. That’s why increasing productivity and workflow efficiency will likely be the No. 1 driver for the adoption of artificial intelligence. Recent BCG study found that genetic AI can lead to significant improvements in workflows, operations and internal tools – participants who used GPT-4 completed 12% more tasks on average and 25% faster than a non-GPT control group -4. Here we will look at ROI first. Let’s call it Horizon 1.
Horizon 2: Customer Experience
This is a great step in the next stage of AI adoption: improving the customer experience. These days, customers expect drastically better – and more personalized – digital experiences. They will turn to your competitor if you don’t remember who they are or anticipate their needs. Generative AI can bring personalization to your digital experiences.
