Artificial intelligence skills The gap is real. A recent study from RandstadThe recruiting firm found that job postings mentioning generative AI skills have risen 2,000% since March. It is the third most in-demand skill set and one of the shortest available.
The logical step for enterprise companies is to appoint a chief artificial intelligence officer (CAIO) to kick-start their efforts. Earlier this year, Dylan Fox wrote Opinion article Arguing that every Fortune 500 company needs a CAIO.
“Companies that do not integrate AI into their products, operations, and business strategies will struggle to remain competitive — and will fall behind those that do,” Fox wrote.
It’s a compelling and logical enterprise-wide argument. But what about others? Startups and startups need to integrate AI just as badly — especially if they’re trying to raise money in this AI moment. However, they often do not have the resources or organizational structure to support a senior executive focused exclusively on AI.
This is where partial AI comes into play. Micro-leadership is a recent workforce trend: experienced executives with subject matter expertise work across two or more clients at a time, offering their talents to fast-growing companies that need their specific skill set but can’t afford it. full time.
Here’s the kicker: a part-time AI officer is better than full-time employment in one crucial aspect. AI—particularly generative AI—is a new technology in which the breadth of experience across many companies gives fractional executives an advantage over their full-time counterparts.
The three stages of adopting artificial intelligence
Although the promise of generative AI is great, it is difficult for companies to establish a reliable measure of ROI early in the adoption curve, especially in an environment where companies are expected to be more conservative in spending.
Increased productivity and workflow efficiency will likely be the first driver of generative AI adoption.
Horizon 1: Workflow efficiency + productivity
Given the market challenges, companies are looking for ways to free up cash and cut spending to keep budgets steady in 2024. That’s why increased productivity and workflow efficiency are likely to be the first drivers of generative AI adoption. newly BCG study found that generative AI can lead to significant improvements in workflows, processes and internal tools – participants who used GPT-4 completed 12% more tasks on average and 25% faster than the control group who did not use GPT-4. This is where we will see the ROI first. Let’s call that Horizon 1.
The second horizon: customer experience
This is a great stepping stone towards the next stage of generative AI adoption: improving the customer experience. These days, customers expect significantly better and more personalized digital experiences. They will turn to your competitors if you don’t remember who they are or anticipate their needs. Generative AI can personalize your digital experiences.