The skills gap in the field of artificial intelligence is real. A recent study by Randstad, a recruitment firm, showed that the number of jobs referencing generative AI skills has surged by 2000% since March. It is the third most sought-after skill set and the shortest in supply.
The Logical Step for Large Companies
The logical step for large companies is to hire a Chief Artificial Intelligence Officer (CAIO) to spearhead their efforts. Earlier this year, Dylan Fox wrote an article advocating for the necessity of a Chief Artificial Intelligence Officer in every Fortune 500 company.
“Companies that do not integrate AI into their products, operations, and business strategy will struggle to remain competitive – and will fall behind those that do,” Fox wrote.
It’s a compelling argument that touches firms at the enterprise level. But what about everyone else? Startups and emerging companies need to integrate AI just as much – especially if they are trying to raise funding in this critical moment for AI. However, these firms often lack the resources or organizational structure to support a full-time executive exclusively focused on AI.
This is where the role of a fractional AI officer comes in. Fractional leadership is a recent trend in the labor market: experienced executives in a specific field work across two or more clients at the same time, offering their talents to rapidly growing companies that cannot afford them full-time.
And here’s the surprise: having a fractional AI officer offers an advantage over hiring a full-time one at a critical point. AI – especially generative AI – is such a new technology that experience in multiple companies gives fractional executives an edge over their full-time counterparts.
Three Stages of AI Adoption
While the promise of generative AI is significant, companies find it difficult to develop a reliable ROI metric early in the adoption curve, especially in an environment where companies are expected to be more conservative with spending.
Increased productivity and workflow efficiency will likely be the primary driver of AI adoption.
Stage One: Workflow Efficiency + Productivity
Given market challenges, companies are looking for ways to free up cash and cut spending to maintain budgets for 2024. This is why increased productivity and workflow efficiency will likely be the primary driver of AI adoption. A recent study by BCG found that generative AI can deliver significant improvements in workflows, processes, and internal tools – participants using GPT-4 completed 12% of tasks on average 25% faster than the control group without GPT-4. Here we will see ROI first. Let’s call this the timeframe 1.
Stage Two: Customer Experience
This is a critical step in the next phase of generative AI adoption: enhancing customer experience. These days, customers expect radical improvements – and more personalized digital experiences. They will turn to your competitor if you do not remember who they are or anticipate their needs. Generative AI can bring personalization to your digital experiences.
In short, startups should consider hiring fractional AI officers. Fractional leadership is a modern business trend: experienced executives in a specific field work across two or more clients at the same time, offering their talents to rapidly growing companies that cannot afford them full-time. This gives them an edge over their full-time counterparts in the field of AI, especially generative AI.
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