How AI in the Workplace is Transforming Business School Education

After using artificial intelligence for more than a decade to fight fraud, the global credit card giant Mastercard is now putting AI to a new use: creating a better workplace.

The company’s HR team, for instance, is leveraging AI and automation to eliminate tedious manual processes and data entry, freeing up team members to focus on more meaningful work. The group’s talent acquisition team has adopted an automated scheduler that seamlessly books job interviews into hiring managers’ available time slots. This simple yet effective solution has accelerated the interview scheduling process by 90 percent.

AI is proving invaluable in other ways. To help create more career mobility for its team, Mastercard is using Unlocked, an AI-based platform that matches employees with short-term projects they can do with colleagues, as well as with mentors, based on their past experiences and desired areas of growth. One goal is to make it easier for the company’s leaders to break out of relying on the same employees for high-priority projects.

So far, the experiment has brought promising results: Ninety percent of employees in the department have joined the platform, and one-third of employees who take part in these short-term opportunities have ended up making an internal career move of some sort, says Michael Fraccaro, chief people officer at the 33,400-employee company, headquartered in Purchase, New York.

“We’re seeing great response from employees on the value the platform brings for networking and personalized paths for ongoing growth and development,” says Fraccaro. “It’s a great tool for supporting our people. And it does just that—supports them.”

While Mastercard is leading the way in harnessing AI to improve workplace operations and employee development, it remains part of a pioneering minority: Despite the growing buzz around AI, only 3.9 percent of companies report actively using it, according to the US Census Bureau, illustrating just how early we are in this transformative journey.

With significantly higher adoption rates in industries like tech—where 13.8 percent of companies report using AI regularly—the technology’s growth is poised to accelerate across other sectors. The rapid rollout of OpenAI’s ChatGPT in November 2022, which reached 1 million users in just four days, has further fueled this trend, notes Jeffrey Schwartz, an adjunct assistant professor of business in the Marketing Division at CBS.

“It happened ‘gradually, then suddenly,’” says Schwartz, borrowing a phrase from a Hemingway character who describes how he went bankrupt. “AI has been coming at us for many decades, but especially the last decade.”

Schwartz should know, having had a front-row seat on AI’s development. He founded the future-of-work practice at Deloitte and has since cofounded and now serves as vice president of talent marketplace Gloat, which made the software Mastercard is using. He is also the author of two books on the future of work: Work Disrupted and Workforce Ecosystems, which he coauthored.

To understand what is ahead in the workplace of the future, Schwartz and other CBS professors have been focusing their research on early adopters like Mastercard. They’re looking at what these companies’ experiences may predict about the workplace of the future, how it will augment and enhance team members’ performance, how AI will influence job design and career evolution, and what questions about responsible use will need to be addressed.

Better Jobs for Some, Reskilling for Others

Under the AI umbrella are several methods of implementation that will affect how many of us work in the future. They include machine learning, which uses algorithms trained on data sets to perform tasks like predicting price fluctuations; natural language processing, where machine learning lets computers understand and communicate using human language; and deep learning, in which computers are trained to mirror people’s neural processes.

Given AI’s evolving capabilities, many leaders are concerned AI will make some skills irrelevant and take people’s jobs, like the machines of the Industrial Age, such as the Spinning Jenny or the assembly line. Some have called for a universal basic income to help displaced workers.

While there’s a lot of debate around how serious a threat there is, the fears have some grounding in reality. Concerned about the need to upskill and reskill displaced workers, a consortium of Big Tech firms, led by Cisco, convened in March 2024 to find ways to connect workers with training and reskilled workers with employers. The group–which includes giants like Accenture, Eightfold, Google, IBM, Indeed, Intel, Microsoft, and SAP–is working with advisors from groups such as the American Federation of Labor, the Congress of Industrial Organizations, and Khan Academy to find ways to help workers stay relevant.

Many workers are worried, too. Following industry-wide layoffs in gaming, attributed in part to the use of AI, one worker who responded to the State of the Game Industry 2023 survey commented, “I think completely eliminating someone’s job is of genuine concern. It should be used to enhance capabilities, not reduce the workforce.”

However, many experts believe the future of AI in the workplace and how it shapes people’s careers will be more complex and nuanced than anyone can predict. Research by CBS professors has pointed to winners and losers in the new economy, with jobs created for highly educated, tech-savvy workers and eliminated for others–who will need to learn new skills or be left behind.

A study by Laura Veldkamp, the Leon G. Cooperman Professor of Finance and Economics at CBS, examines how the adoption of AI and other big data technologies in the investment management industry—an early adopter of AI that she says has served as a “canary in the coal mine”—could result in a 5 percent decline in the labor share of income. This shift has the potential to deepen economic disparities. Veldkamp points out that this pattern mirrors trends observed during the Industrial Revolution, which saw a 5 to 15 percent decline in the labor share of income.

However, her research also found there would be better income-earning opportunities for workers who learned to master relevant tools such as Python and Tensorflow. “At least in this context, AI wasn’t replacing the people–they just got more work done,” Veldkamp says.

Augmenting Professionals with AI

Oded Netzer, Vice Dean of Research and the Arthur J. Samberg Professor of Business at CBS, believes we’re entering an era in which we will see “AI-augmented professionals.” For example, lawyers might use AI to review contracts faster, doctors could use AI to help diagnose diseases based on data analysis, and writers may employ AI to generate content drafts more efficiently.

At the moment, many employers and workers who are still learning how to use AI are looking to AI tools to tackle rote, highly structured and predictable tasks they don’t want to do. For instance, in coding, AI’s ability to predict and autocomplete the next step can be used to make work like debugging code less tedious. “It helps programmers write much faster,” says Netzer. “This raises the question of whether we are going to have [fewer] programmers. I don’t think so. What programmers enjoy doing is not debugging their code but to think about problem solving. AI would require many more programmers to program AI.”

AI is also valuable in helping professionals summarize information, like meeting notes, says Netzer. But what it can’t do, at least not yet, is synthesize data and exercise judgment, he points out—meaning it’s not about to replace humans anytime soon.

“Synthesis is connecting the dots,” says Netzer. “Generative AI is very good at taking data and telling me what’s going on. It almost always fails with synthesis.”

Netzer sees the eventual adoption of AI in more workplaces as similar to how bank tellers evolved after the ATM was introduced. “When ATMs came about, the whole premise was that from now on, we won’t need tellers,” he says. “ The reality was the number of employees in banks actually increased, not decreased. The tasks changed significantly. Bankers did not spend their time handing out cash or taking checks and cash anymore. That was done with ATMs.”

Since then, the jobs once done in branch banks by tellers have been transformed. “They are now spending time in places where the bank makes more money, whether it is financial advising or opening or closing accounts,” Netzer says. “They are not tellers anymore. The tasks changed. It is still customer-facing bankers working at a bank, but with much more interesting jobs.” Though the impact of AI on banking won’t ultimately be known for years, recent data from market research firm Statista shows that the number of full-time employees in the US banking industry rose by several percentage points in 2022, the most recent year for which data are available.

And the pace of change won’t likely be as fast as many people assume, he believes, even as AI gets better. One case in point, he notes, is recent research on teaching children and AI to recognize cats and dogs. The children could do so after seeing the pets five times, on average. For AI, it took 2 million images. “If we understood why a toddler is able to do it, we would teach machines to do the same thing, but we don’t,” says Netzer. “We don’t fully understand how the brain is doing it. Until we get there, it will be hard for AI to make the leaps we do as humans.”

Netzer believes that to help augment the professionals on their teams, employers will benefit from thinking about how AI will impact tasks rather than jobs. “They should identify what AI can do and how employees can take on the remaining tasks that require judgment, decision-making, and complex problem solving,” he says. “Jobs that involve relationship building, strategic thinking, or roles requiring empathy will remain relevant because these areas are challenging for AI to automate.”

Workers worrying about losing their jobs to AI would be better served by redirecting their energy to learning how to use it, he advises.” Paraphrasing a quote from Nvidia CEO Jensen Huang, Netzer says, “You won’t be replaced by AI. You will be replaced by someone who knows what to do with AI.”

Improving Workers' Motivation

In using AI to help workers get things done, employers will need to consider the emotional side of work and take a “human-first approach,” says Stephan Meier, the James P. Gorman Professor of Business and chair of CBS’s Management Division and author of The Employee Advantage: How Putting Workers First Helps Employees Thrive, a newly released book that looks at how building an employee-centric company drives business results.

Jobs will need to be designed in a way that enhances both performance and motivation, he says. 

“AI is often perceived as a tsunami coming to disrupt organizations, but leaders have choices about how to deploy it,” Meier adds. “As a leader, you have the responsibility to employ it in order to enhance human motivation and the work experience, instead of destroying it.”

As he has found, AI can even help on that front, aiding leaders in creating a more personalized and supportive work environment by using analytics to identify communication gaps. It can also provide coaching for managers, helping them tailor learning and development opportunities to individual employees’ needs and motivations–as long as there is transparency, consent, and a focus on improving the employee experience, not surveillance. “AI can be a powerful tool for creating a more intentional and supportive workplace,” he says.

One company Meier and fellow researcher Jeffrey Schwartz studied was Morgan Stanley, an investment bank with 80,000 employees. To augment the services its financial advisors provide, it uses technology that tracks information in the news and personalizes advice for clients. This allows advisors to focus on tasks only humans can do, like having lunch with clients, which is not only more satisfying for the advisors but also grows the business.

“[Morgan Stanley] figured out there are certain tasks that the financial advisor does that the machine can actually do better,” says Meier. “That allows the financial advisor to spend less time on those activities and more time on the ones that are value enhancing, which turns out to be talking to clients and having meetings. Figuring out what is really the human need of their clients is very, very value enhancing, but before AI came into the picture, they were not able to spend as much time on it.”

Beyond the impact on individuals, it is also important to consider the impact on teams’ motivations, according to Bruce Kogut, the Sanford C. Bernstein & Co. Professor of Leadership and Ethics at CBS. Kogut is co-author of a 2023 study looking at how the introduction of AI influences team performance. He and research partners Fabrizio Dell’Acqua and Patryk Perkowski designed an experiment using the Mario Party game on the Nintendo Switch console and found that using AI often backfires when it comes to team performance.

“The main result was that when you introduce AI, performance goes down,” says Kogut. “Whenever it replaces a human partner, it really annoys or depresses the humans. AI does very well, but humans do so badly that the overall team does much worse.”

The only exception is when the humans are highly skilled enough to be competitive with the AI. “If you match highly skilled humans with AI agents, you get a positive outcome,” he says. “That’s reassuring.”

Building Better Jobs

The potential for collaboration between humans and AI opens the door to a new category of roles, which Schwartz refers to as superjobs. In "From Jobs to Superjobs", a 2019 article he coauthored for Deloitte, Schwartz notes that this innovative type of role emerges when technology fundamentally transforms the skills required for a job, as well as the nature of the work and the role itself.

Although new technology skills are required for these roles, superjobs will ultimately create integrated roles that build upon the productivity gains that come when people work with smart machines, data, and algorithms, as he explains in the article.

The idea is that in an ideal world, superjobs could become a “renaissance version” of some- one’s old job, one that allows time to do more of the work that keeps a career interesting and leads to less drudgery—if they choose that. “The general question for employees today is, ‘What is the renaissance version of your job and your career, where you can stand on the shoulders of technology and use it not only to do the same thing faster and better but also to open up time to pursue new things?’” says Schwartz.

That’s not always easy. While it’s fairly simple to break down jobs into tasks—and then ask which can be done by a machine to save time—many leaders and workers have never considered what the ideal version of their job would look like with tedious tasks eliminated.

“The question we all keep coming back to is, ‘What work should people do if they have more time, so we’re not simply doing more of the same work—we’re working for different customers, on different tasks?’” says Schwartz.

With employees expected to work longer due to better health, employers will need to consider questions like this in the context of careers that may last 60 years, not 40. “We have about double the life-span of someone born in 2000 vs. 1900,” Schwartz points out. “Among the people born in the workforce today who are in their 20s, a significant percentage can live to 100.”

The changes AI is bringing will raise the bar on skills development for workers long past college and graduate school. “The half-life of skills gets shorter and shorter, requiring continuous learning,” says Schwartz.

Using AI Responsibly

As more companies try out AI, it’s becoming clear to many that more ethical guardrails will need to be put in place. Before the election, the Biden administration issued an executive order on responsible AI practices, addressing applications like algorithmic hiring to ensure compliance with existing anti-discrimination laws.

With AI building momentum, job hunters on sites such as LinkedIn are already getting a small taste of its influence, with its AI-powered job search suggesting positions that may be a good fit for them.

And that influence is only going to grow. AI will soon be used in workflows to identify suitable candidates, summarize interviews, and recommend potential hires, changing many touch points between applicants and employers, according to Hongseok Namkoong, an assistant professor in the Decision, Risk, and Operations Division at CBS, who studies the interface between machine learning and decision making.

This will bring benefits, like efficiency, but also risks, he says. Modern AI systems, including large language models (a type of AI that can understand and create text in human language), often produce false or incorrect results, known as hallucinations, points out Namkoong.

That can have serious consequences if, for instance, an HR professional assumes it is more reliable than it really is and excludes a qualified job seeker because of what the AI says.

“The problem is you don’t really know when the model is junk, and the model doesn’t know that either,” Namkoong says. “The technology isn’t yet reliable enough to make a series of decisions without human oversight. Responsible AI development is essential to improving reliability.”

Companies like Mastercard are taking factors like this into account as they prepare their workforce for the future. The company has created forums for ongoing discussions of trends, technologies, and safeguards, and is taking steps to ensure employees know its current use cases for AI, including its commitments to ethical AI and data privacy. It holds regular fireside chats with executives on a broad range of topics surrounding AI. And most recently, it launched an AI and Data learning series with curated offerings for beginners, experts, and those in between.

“We know testing and learning with AI is a journey,” says Mastercard’s Fraccaro. “Some people are just starting out and others are much further along. Our goal is to support people where they are, as we navigate the AI journey together.”

Given AI’s potential, it’s a journey likely to be filled with many unexpected lessons for Mastercard, Morgan Stanley, and many other employers–and their employees–for decades to come.