Q&A: ManpowerGroup exec explains how to manage an AI workforce

Generative AI (genAI) projects will move from pilot phase to production for many companies this year, which means the workforce will be affected in ways never before imagined. One of those ways will involve onboarding AI agents as new digital employees.

One of the focus areas for global staffing firm ManpowerGroup has been its proprietary platform, Sophie, which leverages AI to tackle talent screening tasks. The staffing firm sees AI agents as playing a central role in sifting through job applicant data for clients, identify market trends, and offer job applicant suggestions. When Sophie provides a recommendation — either for or against a candidate — it also explains the reasoning behind it. 

“We view Sophie as a partner to help you focus on what truly matters: finding the right people and building a workplace grounded in honesty, respect, and mutual confidence,” said Carolyn Balkin, general manager for Global Client Solutions at ManpowerGroup.

Professional services firm Accenture has even developed a program for onboarding agentic AI digital “employees” to help “agents make the right connections and provide feedback to improve their performance.”

The company borrowed a page from its HR best practices on team integration to ensure agents were introduced to the marketing team and understood their roles. It also created feedback loops that enabled simple, two-way feedback between human marketers and agents, which turned out to be key in establishing “collaboration and mutual learning.”

AI adoption also means that practically every employee, whether they’re part of an IT organization or a business group, must become familiar with chatbots and other large language model-related technology to better do their jobs.

What organizations are seeking in new talent has shifted as AI continues to take on the more repetitive predictable tasks, requiring workers to focus more on creating new business value.

ManpowerGroup’s Balkin manages IT, technology and telecommunications industry vertical clients, and she has been advising organizations about what it means to manage AI employees. One of the biggest challenges: finding the kind of talent they’ll need that can work with AI and figuring out how to integrate agents across business groups.

Carolyn Balkin, general manager for Global Client Solutions at staffing firm ManpowerGroup
ManpowerGroup

How has managing employees changed since the adoption of AI in the workplace? “I think you know that’s where the soft skills have really come into play, because it is not just a technology. I was at the Davos Conference recently, and a lot of the conversations were about AI, and a number of organizations talked about. It’s not just a technology anymore. We are looking for individuals that have the industry experience. We can take somebody with industry experience and train them on the technical part of the job.

“It’s a lot harder for us to take somebody with the technical skills and teach them how the industry works. I think there’s a focus on looking at the soft skills: the problem solving, the complex reasoning ability, and communications. Because it’s not just developing AI for the sake of software technology; it’s to address that larger business problem. It’s about looking at all of the business functions, and taking all of that into consideration.

“So, I think it is more than just the technology play now. And therefore, when managing these people, it’s not just managing a technical group anymore. You’re managing people who are bringing a different perspective, a different experience, and different soft skills to play, and it’s about how do you pull all of that together.”

How do you go about managing that other type of AI employee — the digital agent, or the AI itself that is becoming another kind of employee? “We do have some early adopters that have put in place these agent workforces. I do know it has changed how they’re looking at workforce management. It’s about what can my agents do? You’re almost looking at agents as the new intern of the company. What can the agents do transactionally, and then what skills do I need to manage that on top of the agents? So, what technical skills do I need, and what soft skills do I need in my employees to manage those agents? And that becomes the workforce plan.

“Then it’s looking at location strategy. In the past, organizations have led with location in the past; now, it’s about getting the agent strategy right. First, figure out what you can take from your transactional workers and then focus on what skills you need.

“Then you have to consider employee upskilling or reskilling. I think organizations are going to have to become much more proactive on their upskilling and reskilling programs. We’ve heard so much about this for the last couple of years, and I think there’s a gap where organizations believe they have strong programs. But when you talk to employees within these companies, they don’t feel there’s been the opportunities to upskill and reskill. So, I think we’re going to have to see more structure around those programs.”

So, how are you managing the digital employee you call Sophie? “Behind Sophie is a cross-functional group that bridges technical expertise and real-world understanding. AI and machine learning experts collaborate with sales and operational professionals, along with individuals who study how people interact with technology. Together, they work toward maintaining our commitment to fairness and trust by:”

Running ongoing checks to spot hidden biases in how Sophie interprets data.

Protecting personal information through strong security protocols and compliance practices.

Offering transparent decision-making details so you always see why Sophie has chosen a particular path.

So would you say managing your digital workforce or managing your agentic workforce is kind of the next frontier? “I definitely think so. I mean, it’s just a collaboration across the agents. And look how fast AI came on board, and now it’s just getting smarter and harder. You know how it’s collaborating with each other. And you know, you have to teach it, too. It’s not going to be just like humans. It’s not going to be 100% accurate, so you need to monitor it; it’s going to create different jobs. You know, back to your question, will it create jobs or kill jobs? Don’t know yet.

“I think they’ll definitely be different, though, because now you have people looking at the quality of what’s coming out of the agents, testing to see if it’s accurate, training the agent. So it will create a whole new set of roles, and it’s going to affect every industry. In manufacturing, for example, organizations are using AI agents for quality control, and doing things significantly faster than they’ve been able to do in the past.”

What industries are being affected the most quickly? “I would say it’s your tech companies that are probably the early adopters, because for them to sell something, clients want a case study. They want to know where you’ve done this and what the impact has been. So, the tech companies see themselves as client zero in order to demo a lot of these new tools and technologies.”

What kinds of problems is AI introducing from an employee management standpoint? Do you believe every company is a technology company and every employee is a technologist to some extent? “Technically, yes, I do believe that. The problem is [that] the gap is getting wider between those employees who understand AI technology and are willing to learn more about it and those who don’t want to have anything to do with it. But I think everybody will be a technologist, eventually. It’s going to be talent augmented by technology.

“I was recently talking to a business manager, and he said while there’s always going to be an IT group, it’s no longer going to be the harbinger, or the only ones who own the technology.”

You have people in marketing, in advertising, in customer support, all the various branches of a business that need to be tech savvy. What’s needed to manage a workforce where everyone is using AI in one form or another? “I think you need a lot more collaboration across the workforce, because historically it has always operated in a very siloed way. You’d roll technology out from one place to the rest of the organization. As you adopt more AI, you can’t do that anymore.

“A big topic at the Davos conference was agentic AI, and that is really all about collaboration. A lot of the large language models — generative AI — have been historically working in a silo. You ask it a query; it shoots out an answer to you.

“The AI that’s under development at a lot of these organizations today is more the agentic AI, which is collaboration of various AI apps and a collaboration of your various data sets. So, that creates a lot more questions because you’ve got to have governance of all those agents. You’ve got to have platforms and the technology behind that.

“There has to be the governance model in play. You need to look at the business holistically in order to manage AI across all of those areas, so you don’t have department doing one thing that might conflict with what another may be doing. They all really need to be aligned so that they’re functioning with each other.”

Anecdotally, when I talk to folks who are out of work, even people who have years of experience technology, they’re having a hard time finding jobs. What do you see happening? Is it harder to get a technology job now, and what skills are companies looking for? “I think it is harder to land a technology job right now. And I think part of that might just be a reflection on where the market is. I know there’s been a lot of stability in the IT tech sector, but organizations haven’t been hiring on additional talent. And some of that is 2024 seemed to be a settling period where there was a lot of adoption of AI. This year it’s about the impact of AI. And I think organizations, No. 1 are trying to figure out. What does their workforce look like? Where do they need to bring in additional talent?

“And then No. 2, what does that talent look like? And I don’t think they’re there yet. Then you throw in the whole agent workforce, and that adds to the problem.

“There are more mature companies when it comes to AI — the IBMs of the world, the Accentures, the Salesforces; they’re looking at how AI agents are becoming part of their workforce planning. When understanding what your needs are, you first have to consider what the agents will cover those needs, and then figure out what employee skills are needed on top of them.

“And I think that’s the other piece — from a management perspective, it’s become more multifaceted in the approach that companies are taking. They’re not looking for job- centric people anymore. It’s more about the skills-people have.”

When you say less job-centric, what does that mean? “In the past, you would post a job and it would list the tasks of the job. Now, managers are focused more on skills needed to perform in their business. So, these are the skills that we need to support the project.

“I actually had an interesting conversation with a client yesterday, and they were even talking about soft skills, with AI becoming more front and center when it comes to reasoning and problem solving. You assess that along with the technical skills an employee brings to the job. Businesses are looking at assessments that can help them evaluate the soft skills, some of the cognitive reasoning skills [potential hires have].”

Data shows that the number and types of jobs are growing with the advance of AI, but at the same time, there is evidence AI is reducing employee headcount — taking on tasks formerly done by employees. Which do you believe it is? Or is it both? “Is AI is going to reduce workforce sizes, lead to more people being laid off, or is it going to create more opportunities? It’s hard to say. I mean, it could go either way. But I think it’s going to impact more of the transactional roles. It will take a lot of the low-level transactional work away, but what it will also do is allow people to focus on those specialized skills.

“We’ve been talking about how software development is happening so much faster with AI. So, companies are looking for more specialized skill sets. I think there’ll be a shift from the generic skills that companies brought on in the past to more specialized skills that they’re going to need in the future.”

Can you give me some examples of the specialized skill sets? “For example, SAP engineers, SAP architect, AWS skills, and Salesforce skills. Those are some of the software areas that companies are looking for more specialized talent.”

So, you’re saying hiring will be based on skills that are specific to the applications and the AI that is becoming a part of that? “Even cybersecurity. While we’ve been talking about software, cybersecurity is another area that’s going to be very important because you’re opening up some doors with AI related to security and data privacy.”

Where do you even start with that cybersecurity and AI? It seems almost amorphous if AI is in every corner of a business. “There are so many things, and it’s happening so fast. So, we are still learning as fast as we can. We’re trying to understand what the impact of AI will be, and how it will change our business models. Even from a talent organization like ours, which is providing global talent solutions, what does that do for us?

“Now, our company is going to start looking for your talent plus the AI agents you’ll need. So AI becomes part of a hiring solution. There are a lot of companies that are developing AI boot camps for the C-suite executives and opening their eyes to what’s out there. Think about it. At universities like MIT, it used to take teams of scientists years to develop what can now be done in a matter of seconds.

“Right now, companies are taking a step back to discover what the business challenges are that need to be solved because of AI automation. They’re trying to discover the best way to do that. I don’t think there’s a lot of academia programs developed for that. I think a lot of it is pilot programs that involve peers talking about the issues.”