Recent studies from Randstad Recruitment indicate that the AI skills gap is real. AI-related jobs have increased by 2000% since March. It is the third most in-demand skill set and the least available.
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 fail to integrate AI into their products, operations, and business strategies will struggle to stay competitive and will fall behind those that do,” Fox wrote.
It’s a compelling and logical argument at the enterprise level. But what about startups and growth-stage companies? They are in dire need of integrating AI—especially if they are trying to raise funding in the current climate. However, they often lack the resources and organizational structure to support hiring a senior executive focused exclusively on AI.
This is where the fractional AI officer comes in. Fractional leadership is a modern trend in the job market: experienced executives in a particular field work across multiple clients simultaneously, bringing their talents to fast-growing startups that need their specific skill sets but cannot fully afford them.
And here’s the surprise: having a fractional AI officer is often better than a full-time hire in one critical aspect. AI—especially generative AI—is such a new technology that the broad experience across competing companies that fractional executives bring gives them an edge over their full-time counterparts.
Three Stages of AI Adoption
While the promise of generative AI is significant, it can be difficult for companies to create a reliable measure of return on investment in the early stages of the adoption curve, especially in an environment where companies are expected to be more cautious in their spending.
Improving productivity and workflow efficiency will likely be the primary driver of generative AI adoption.
Given the challenges facing markets, companies are looking for ways to free up cash and reduce spending to keep budgets tight in 2024. For this reason, improving productivity and workflow efficiency will likely be the primary driver of generative AI adoption. A recent study from Boston Consulting Group found that generative AI can deliver significant improvements in workflow, processes, and internal tools—with participants using GPT-4 completing 12% of tasks at a 25% higher rate than the control group that did not use GPT-4. This is where we will first see a return on investment. Let’s call it “Horizon 1.”
Horizon 2: Customer Experience
This is a crucial 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 switch to a competitor if you fail to remember who they are and anticipate their needs. Generative AI can bring personalization to your digital experiences.
Source: https://techcrunch.com/author/catherine-shu/
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