The skills gap in artificial intelligence is real. A recent study from Randstad, a recruiting company, showed that the number of jobs indicating generative AI skills has increased by 2000% since March. It is the third most in-demand skill set and the shortest in supply.
The Logical Step for Large Companies
The logical step for large companies is to appoint a Chief Artificial Intelligence Officer (CAIO) to kick off their efforts. Earlier this year, Dylan Fox wrote an article advocating for the necessity of appointing 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 stay competitive – and will fall behind those that do,” Fox wrote.
It is a compelling argument that touches companies at the corporate 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 current environment. However, these companies often lack the resources or organizational structure to support hiring a senior executive focused exclusively on AI.
This is where the role of the fractional AI officer comes in. Fractional leadership is a modern trend in the job market: seasoned executives in a particular field work across multiple clients simultaneously, providing their talents to rapidly growing startups that need their specific skill sets but cannot afford them full-time.
And here’s the astonishing thing: having a fractional AI officer is better than hiring a full-time resource in one critical area. AI – especially generative AI – is such a new technology that broad experience across several companies gives fractional leaders an edge over their full-time counterparts.
Three Phases of AI Adoption
While the promise of generative AI is substantial, it is challenging for companies to create 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 are likely to be the primary drivers of generative AI adoption.”
Horizon 1: Workflow Efficiency + Productivity
Given the market challenges, companies are looking for ways to free up cash and reduce spending to keep budgets flat in 2024. For this reason, increasing productivity and workflow efficiency will likely be the primary driver of generative AI adoption. A recent study from BCG found that generative AI could achieve significant improvements in workflows, processes, and internal tools – participants using GPT-4 completed 12% of tasks with an average of 25% faster than the comparison group without GPT-4. Here, we will see ROI first. Let’s call this Horizon 1.
Horizon 2: Customer Experience
This is a great step toward the next phase of generative AI adoption: enhancing customer experience. These days, customers expect significant 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 trend that must be taken seriously, as experienced executives can provide valuable contributions to growing startups that need their specific skills but cannot afford them full-time. Thanks to their experience across multiple companies, fractional AI officers gain an advantage over their full-time counterparts.
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