This is Digital, Episode 43: Viewing AI as Talent, Not Technology

Q&A

Can you explain how shifting mindsets around AI can unlock AI’s full potential? How does a change in perspective accelerate value creation and help businesses move from struggling with isolated solutions to fully realizing the power of AI?

Steven: I think you have to step back a little bit in terms of how that mindset can do that. AI isn’t replacing what employees do—it's enhancing and augmenting what they do. You have to think of it as improving things at the task level. That's what we're trying to help people understand—when you train everybody to use AI tools—in this case, prompt engineering—you're helping them across a range of activities. When you see it at that level, you recognize that training your employees may be the most important thing—that it is a type of talent. 

The metaphor we use that helps this concept click is that training your employees to be prompt engineers is like giving everyone an intern. We all have to check an intern's work, but we love having them perform busy work so we can focus on the more value-added stuff. So, training everyone to be a prompt engineer is like giving them a very special intern who has access to all human knowledge, has perfect memory, and gets smarter every year, helping your employee throughout their career. That helps people understand that by training their employees, they can unleash anywhere from 10-15% improvement in productivity across their entire employee base, without putting in any proof of concept. 

Implementing new AI tools, integrating AI into products, or finding the latest AI innovation is something that’s commonly talked about, but training every employee to be a prompt engineer might not be on many people’s radars. How many companies are actually considering this? And for those that do, what does the process look like? How long does it take to see results?

Brigitte: If we start with how many companies are seriously considering and willing to invest the time and resources into training all of their employees, quite honestly, it's very few. So, what does that mean? People running around in the Wild West, getting outputs and putting them in front of their organization, but there's no appropriate quality checks or training involved to make sure good things are happening. 

The big issue is people are using AI but might not know the right way to use it. There’s a lot of risk simmering under the surface, and many companies are not looking at training as the solution. You might get a tool or set up a governance model, but without helping people develop the skills, there's going to be a delta between the investment and results. AI is not just a technology but a completely different way of working that involves changing how we problem-solve, think critically. If we don't adapt those skills, we won't see a return—and worse, we open ourselves up to risk. 

We have work that needs to be done, and there are many different ways and talent types to accomplish that work, each with its trade-offs. You choose the correct resource at the right time to deliver the value. It’s the same framework. And if we don’t treat AI in that integrated, holistic way, we’re missing the mark. 

We've discussed the different types of talent and how AI fits into that. Can you describe the various types of talent and how we can help clients determine the best way to utilize them?

Steven: To make this real, it’s important to recognize that no single individual in our client organizations manages all talent types—HR oversees employees, IT handles contractors, and AI is focused elsewhere. We need a framework that identifies the right talent for each role based on associated activities. This framework helps organizations align their talent strategy going forward. As AI continues to evolve, it will drive improvements across all talent types. Employees will become more efficient through AI integration, and contract labor will see enhanced productivity as well. Additionally, outsourcing providers are investing heavily in AI solutions, and organizations should follow suit.  

Brigitte: I love that the strategic workforce optimization framework mirrors the complexity of managing a household. Just as we consider trade-offs—like who cooks dinner or uses a Roomba to vacuum—we apply similar principles at the enterprise level. It’s about optimizing tasks and resources to achieve balance. If we don’t approach this holistically, as we do in our homes, how can we effectively understand and manage those complexities in an organization? 

As generative AI has come on the scene, how much has it transformed the way enterprises operate? Are companies able to completely rethink how they function, not just in terms of saving money, but in truly doing things differently in ways they never could before?

Steven: I think it's completely different. We're trying to help people understand that AI is not technology in the traditional sense; it’s a talent type, and it changes everything. Importantly, this is only the beginning. The power we gain from prompt engineering super users will continue to increase throughout their careers. 

Beyond the dollar savings for clients, there’s a significant qualitative improvement in employee satisfaction. They can complete tasks more accurately and efficiently, which allows them to focus on higher-value work. 

At West Monroe, we send a Net Promoter Score survey to every client upon project completion. We’ve long been known for our world-class results, averaging 80% NPS. This year, however, the practice that involved AI training saw its NPS scores jump into the nineties. For us, this is a game changer in how we improve our delivery.