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The A.I. revolution is well underway. Yet many companies are struggling to figure out how to adapt to the new world, and especially how to train and skill their workers.
Technology and consulting firm Accenture announced a three-year, $3 billion A.I. investment in June, and recently appointed Lan Guan as its inaugural chief A.I. officer. She will lead the firm’s overall A.I. strategy, including doubling its A.I. talent to 80,000 human workers through training current employees, corporate acquisitions, and recruiting from major universities.
Guan, who served as a senior managing director and global data and A.I. lead at Accenture before taking on the new title, spoke with Fortune about how the professional services firm is hiring and developing its staff for the A.I.-driven future.
This interview has been edited and condensed for clarity.
Fortune: Accenture recently announced a $3 billion A.I. investment, including doubling its A.I. talent to 80,000 people through hiring, acquisitions, and training. How does your new role fit into delivering on this commitment?
Lan Guan: On the talent front, we are doing a couple of things, because we realize that’s a pretty hefty goal, from 40,000 to 80,000. We have to create multiple pathways for us to get there. On the upskilling front: How do we define a couple of pathways so that we can take some of our existing people, who may have done a lot of data work…[and] strategically train them up? Send them through our Gen A.I. Academy [an in-house educational initiative], so that they can take different courses, different tracks. We also want to make sure we set up this program so folks, post-training, get on-the-job practical shadowing to learn from the experts.
The second part is venture and acquisition. We’re constantly looking at different acquisition targets. Based on the strategy that we have, we want to make sure that we’re bringing in the venture and acquisition firms to help us beef up the talent agenda to add some of the niche capabilities that we’re looking for.
And then on hiring, we’re [bringing in] a research scientist team. We’re hiring top-notch talents from the market, from top academic institutions, from some of our tech partners, so that we can bring in experts…so that we can best leverage our industry expertise.
Can you share a bit more on specific training programs, policies, or plans that you have in place for skilling existing talent for A.I.?
We are setting up multi-stage training programs.
First of all, everybody at Accenture needs to take our technology quotient (TQ). It’s a technology learning program that we’ve been using for the last couple years. But A.I. has always been one of the hottest topics, so now we’re leveraging the platform, the infrastructure, basically adding the generative A.I. So to me, that’s the first objective: to give this kind of grassroots level training.
The second level is what we call the Gen A.I. Academy. This is our flagship program for learning everything related to A.I. It’s very thematic, very role based. So you can learn data foundations, different modeling techniques, large language models, specific kinds of prompting and fine-tuning, infrastructure power, you can learn A.I. ethics.
The third part is almost like a capstone [where we] leverage our partnerships with top academic institutions, like Stanford University, MIT, Carnegie Mellon University, [and] the Alan Turing Institute. For example, I created the Accenture Stanford Foundation Model Scholar Program. We just did our inaugural program in July. So now we are sending our practitioners to this multi-day training to learn from the best of the best.
How can companies better integrate A.I. with the HR function?
I say to so many clients, you cannot treat this as a technology subject. You just cannot. Usually, after we talk about the disruptive power of the technology, we will show [clients] that based on our research, 40% of working hours will get impacted by generative A.I. And then we show them [the] industry-by-industry cut. That’s a light bulb moment.
My HR clients [have] started thinking about: How do I do workforce planning? How do I effectively train our people to pivot to this new technology? What is that cultural shift that I should get ready for? How do I articulate adoption? Oftentimes, people are willing to play with this generative A.I. technology, but for them to overcome the mental barriers [and] use on a daily basis, it’s a huge culture shift.
Success with generative A.I. requires equal attention on people and training as it does on technology. Companies should therefore dramatically ramp up investment in talent to address two distinct challenges: creating A.I. and using A.I. This means both building talent in technical competencies like A.I. engineering and enterprise architecture, and training people across the organization to work effectively with A.I.-infused processes. Even domain experts who understand how to apply data in the real world (a doctor interpreting health data, for example) will need enough technical knowledge of how these models work to have confidence in relying on them.
I recently wrote about how a lot of HR leaders are interested in A.I. investment, but struggle to get buy-in from the CEO. How can HR leaders really secure that support?
Demonstrate how generative A.I. will impact the entire value chain, from mapping generative A.I. technology…to the entire talent journey. This is the approach that we use to gain buy-in from not just the CHRO, but also [the] CEO of the client, so they see that this is not just a technology conversation. This is a huge amount of disruption that you need to be able to manage. Showing them how to map to the talent journey, I think it’s a very methodical approach that seems to be working very well.
And show the R.O.I., right? The productivity gains, show the business case. We always joke about [how most] of the jobs that we have today, 80 years ago, did not exist.
Paige McGlauflin
paige.mcglauflin@fortune.com
@paidion
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