A lack of staff for booming interest in AI
With new development around generative AI like OpenAI’s chatGPT, business leaders repeatedly refer to artificial intelligence as a focus for the future. So, how do companies find AI staffers and how can you secure a job in AI?
There aren’t enough skilled professionals available, even with the recent contraction across the technology industry, consultancy McKinsey says in a blog post.
A typical AI project requires a highly-skilled team including a data scientist, data engineer, machine-learning engineer, product manager, and designer.
Companies are increasingly hiring directly from bootcamps and training academies, regional tech companies, and professional organizations, according to McKinsey.
“As employers we have to think creatively about how we find talent and develop a meaningful apprenticeship journey to help them develop skills as role requirements change, which can be as frequently as every six months”, says partner Helen Mayhew, co-author of the companys research report The state of AI in 2022.
The AI space is evolving quickly with a greater specialization in roles. One example is the machine learning engineer who designs, builds, and productionizes predictive models and AI systems for automation, performance, and scalability, the blog post says.
“When it comes to sourcing AI talent, the most popular strategy among all respondents is reskilling existing employees. Nearly half of the companies we surveyed are doing so,” says Alex Sukharevsky, co-author of the companys report on the state of AI.
He says that as technicians progress to more senior levels, they often specialize in an industry or function.
And also in the AI sector, there is an obvious need for better gender and ethnic balance.
“With the scarcity of talent, needless to say, the research findings on diversity are concerning,” says Helen Mayhew.
The average share of employees on AI teams at respondents’ organizations who identify as women is just 27%; the share is similar among the average proportion of racial or ethnic minorities: 25%.
“Diverse and inclusive perspectives are especially critical in AI to prevent issues of bias in datasets and models, and distrust in outcomes.”
The blog says that looking ahead, as companies evolve their strategies for developing AI tech talent, they may find lessons that are applicable to other parts of their business.
“The newest wave of generative AI models, for example, promises to reinvent functions such as communications, sales, and human resources.”
The report says that after a period of initial exuberance, there has been a plateau in AI adoption.
“A course observed with other technologies in their early years of adoption,” says partner and lead-author of the report, Michael Chui.
“We might be seeing the reality sinking in about the level of organizational change it takes to successfully embed this technology,”
In 2017, 20% of respondents reported adopting AI in at least one business area. After peaking at 58% in 2019, it’s dropped to 50% today.
“This tailing off is not about saturation; most organizations haven’t yet maximized the opportunity of the technology, according to our research. It’s that companies aren’t investing in the resources needed for the organizational change required to effectively implement AI. One reason is that there’s a talent crunch”, the blog post says.
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