The skills gap in the field of artificial intelligence is real. A recent study by Randstad, a recruitment company, showed that jobs mentioning skills in generative AI have increased 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 kickstart their efforts in this area. 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 and logical argument at the level of large companies. But what about startups and growth-stage companies? They need to integrate AI just as much – especially if they are trying to raise funding in the current period. However, these companies often lack the resources or organizational structure to support hiring a senior executive focused exclusively on AI.
Here is where the role of the fractional AI officer comes in. Fractional leadership is a recent trend in the job market: experienced executives work across multiple clients simultaneously, offering their talents to fast-growing startups that need their specific skill set but cannot afford it full-time.
And here is the key point: having a fractional AI officer is better than full-time hiring at a critical juncture. AI – especially generative AI – is such a new technology that extensive experience working with multiple companies gives fractional executives an advantage over their full-time counterparts.
Three Stages of AI Adoption
Although the promises of generative AI are significant, it is difficult for companies to create a reliable ROI metric at an early stage of 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 primary driver of generative AI adoption.
Horizon 1: Workflow Efficiency + Productivity
Due to market challenges, companies are looking for ways to free up cash and cut spending to keep budgets stable in 2024. For this reason, increasing productivity and workflow efficiency will likely be the primary driver of generative AI adoption. A recent study by BCG found that generative AI can drive significant improvements in workflows, processes, and internal tools – participants using GPT-4 completed 12% of tasks with an average speed 25% faster than the control group without GPT-4. This is where we will see ROI first. Let’s call it “Horizon 1.”
Horizon 2: Customer Experience
This is a great step toward the next stage of generative AI adoption: enhancing the customer experience. Nowadays, customers expect radical improvements – and more personalized digital experiences. They will turn to your competitors if you do not remember who they are or anticipate their needs. Generative AI can bring personalization to your digital experiences.
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