$1 billion! $2.5 billion!! $3 billion!!!
No, it’s not the world’s most expensive luxury-yacht auction. It is the amount of money PwC, EY, and Accenture respectively have promised to invest in AI over the next three years.
A lot of this cash is, somewhat ironically, earmarked for people. For instance, Accenture wants to double its AI-focused staff from 40,000 to 80,000. IBM announced a center of excellence for generative AI.
There’s been a lot of attention spent on how talent acquisition professionals will use AI to hire. It’s the shiny toy in the recruiter’s toolbelt, promising efficiency, speed, and accuracy. A brighter future, a better tomorrow. Yes, yes, yes, of course. It’s all very exciting.
If you buy the predictions of these same consultant groups, millions of jobs will be disrupted or replaced by AI. But who is going to use these new technologies, and how will they be able to get the most from them?
At Accenture, Lan Guan is the chief AI officer for the organization, and she is tasked with doubling its AI talent. In a recent interview with Fortune, she covers some of the challenges she is facing.
Tech companies have been hiring the data scientists and software engineers behind AI for literal decades. These roles have been in high demand so long, it’s starting to feel like this is the demand for this talent.
But companies like Guan’s are looking for AI specialists and AI-adjacent talent, too. Yes, they need research scientists from top companies and universities, and they need technical expertise. But they also need people who are fully trained on how to use AI to its best abilities and to stay constantly updated because the landscape is shifting so rapidly.
Hiring AI-adjacent talent is not as simple as posting a job ad and waiting for applications to roll in — as if that works for anything with specialization. It requires a deep understanding of the AI landscape, a clear vision of the role AI will play in the organization and the job, and a strategic approach to sourcing, attracting, assessing, and retaining AI talent.
For companies that sell AI solutions, the question has always been about technical talent. Do they have the smartest people to build the smartest solutions fast enough? A talent grab for data and engineering folks with any background in AI seemed to accelerate.
That’s not enough, though.
Any company that hopes to use AI needs to be rethinking its hiring process. Hiring for AI is not just about filling a specific role but about building a team that can drive AI innovation and deliver tangible business results. That means considering technical and soft skills side by side. Problem-solving, critical thinking, ethics, and creativity are all unique attributes that people bring to the use of AI at work.
The value of AI a few years ago was all about the algorithms and data a select few organizations could really take advantage of. Tomorrow, the value of AI will be in the human minds that train, deploy, and use these tools to get real work done. That’s what consulting giants (and other organizations) can’t miss out on. It’s why they are pledging billions of dollars — even if pledges like that are often cynical ploys for PR and investors.
At Accenture, they aren’t just hiring 40,000 people. Sure, hiring new talent can bring fresh perspectives and specialized skills to the team. However, with the high demand and limited supply of AI talent, this isn’t a simple task. Even a company with pockets as deep as Accenture couldn’t do that.
They are also upskilling employees with data backgrounds with in-house development opportunities (perhaps realizing that hiring might be a challenge). This can be useful, especially if employees are going to be displaced or if some are looking for new opportunities. Still, the amount of resources it takes to spin up an internal program can be enormous.
Acquiring companies with the necessary skills can be a shortcut to gaining AI expertise. However, this approach involves significant costs and risks, including cultural integration and retention of the acquired talent. Moreover, it requires a deep understanding of the AI capabilities of the target company and how they align with the acquiring company’s AI strategy.
Even in hiring talent acquisition contributors and leaders, more emphasis needs to be placed on their familiarity and experience with the AI tools that they may be using on a daily basis. Misuse of AI in hiring has negative consequences for everyone — candidates, employees, recruiters, and the organization as a whole. The success of your AI- and automation-driven hiring process begins and ends with the people who will be at the controls.
And that’s true for the entire organization, too. If companies really want to get the most out of these new innovations, they need to hire people (and train, and retrain) who are fluent in or are willing to become fluent in how to use these tools for maximum success.
