How the Next Generation of Managers Is Using Gen AI

It has become common to hear the statement “AI won’t replace managers — managers who use AI will replace managers who don’t use AI.” We strongly agree with this sentiment, but clearly this new paradigm hasn’t arrived yet.

Only 15% of leaders and managers consistently use generative AI in their daily work, according to a forthcoming Capgemini Research Institute survey of more than 1,400 leaders and managers. Our direct experience also confirms that many managers are unaware of the potential of gen AI in various aspects of their roles, from preparing for important meetings to analyzing different perspectives and trade-offs on business issues.

Given this low rate of adoption among today’s managers, it’s worth considering the situation for tomorrow’s managers. As new managerial talent prepares to enter the corporate workforce, are they more adept at using gen AI?

How Are Management Students Using Gen AI?

Over the past few months, we posed this question to more than 200 MBA and Master in Management students (aged 23-30) at selected five European and North American universities. Our aim was to investigate the frequency with which these student used gen AI, the types of models they used, and the specific tasks for which they used it.

We found that 40% of these students use gen AI multiple times a day. These data are in line with other recent studies focused on university students in the UK and U.S.

To gain a more detailed understanding, we conducted workshop sessions and in-depth interviews with a group of 30 graduate students. We found that they are using gen AI in two modes: as an executor (helping with writing, summarizing, coding, translating, and information retrieval) and as a thought partner (for brainstorming, problem solving, or challenging ideas). They experiment with gen AI on a wide range of tasks, gradually building new capabilities. They also demonstrate a good level of awareness of gen AI’s limitations and risks, using appropriate practices, such as providing necessary contextual information to the AI, adopting a conversational mindset, and exercising critical judgment to avoid overreliance on the technology.

Our findings confirm that these students are equipped to apply their gen AI capabilities in the workforce. But our latest data on gen AI in organizations reveals a potential problem: Nearly 40% of organizations authorize only chosen groups of employees (usually those in specialized and technical roles) to use gen AI tools. When the students we surveyed join the workforce, their enthusiasm to put gen AI to work will be tempered, and they may experience frustration. Moreover, we found that these students experiment across more than a dozen public gen AI tools, but only 7% of organizations allow them to choose their gen AI tools at will. A majority of organizations (54%), mandate that employees must use only authorized generative AI tools within specific guardrails.

It’s worth stating the obvious: We are not talking about a far-off future state — most of these MBA students will be back in the workforce within the next year.

4 Ways Organizations Should Respond

We discussed these issues in roundtable conversations with senior executives and board members of five global companies in various sectors including chemical, banking, and retail. The group identified four strategies organizations and their leaders should adopt to attract and retain these future gen AI-savvy employees:

How companies can be a magnet for Gen AI talent

When it comes to presenting the employer value proposition to these gen AI talents, it’s not enough to declare AI’s relevance; organizations need to provide concrete evidence of gen AI integration into workflows, demonstrating its adoption and regular use by workers and managers.

Leading companies have publicly communicated how they are incorporating gen AI models such as ChatGPT Enterprise or Microsoft Copilot in their work processes. At Novartis, for example, HR professionals use ChatGPT Enterprise for tasks such as writing job descriptions for new roles or drafting communications about policy changes, using gen AI as a starting point rather than beginning from scratch. Moderna demonstrates its “embrace gen AI” approach by providing access to the tool and the freedom to innovate across all company functions, from clinical trials to legal department to corporate branding. More than 750 custom GPTs have been developed across functions, with each user averaging 120 ChatGPT Enterprise conversations per week.

Some companies are attracting the new generation of GenAI-ready talent is to engage them at universities rather than waiting for them to come to your door. One approach is to collaborate with business schools on projects and assignments that involve students. For instance, at the Collège des Ingénieurs (CDI), one of the MBA schools in our study, a dozen business leaders from large companies in sectors such as chemicals and retail collaborated with 50 young fellows of STEM background in an AI hackathon sponsored by the Dieter Schwarz Foundation. Divided into eight teams, the students used ChatGPT 4.o to solve business problems ranging from helping marketing managers with customer segmentation, to helping procurement managers explore scenarios for new sustainable packaging, to helping account managers improve their value-pricing skills.

“For me, it was an eye-opening experience to see how adept these young talents already are at using gen AI as a thought partner,” said Gaetano Blanda, head of Evonik Animal Nutrition. “They showed us how to dialogue with the machine on a variety of challenges, from customer engagement to supply chain sustainability.”

How companies can onboard and engage Gen AI talent

According to Microsoft and LinkedIn’s 2024 Work Trend Index, 71% of leaders are more likely to hire a less experienced candidate with gen AI skills than a more experienced candidate without them. Unfortunately, when these highly sought-after new hires join the company, they can quickly become frustrated and disengaged when they discover a lack of access to gen AI tools or find themselves stuck in outdated work processes.

To reduce this risk, employers should prioritize applications of gen AI to employee experience, starting from the onboarding process. By leveraging gen AI as a supportive onboarding tutor, new hires can more effectively familiarize themselves with company documents, policies, and schedules, and gain a better understanding of the organization, market and customer needs. This approach helps alleviate the anxiety of appearing incompetent in front of managers and reduces disruption to colleagues. New hires can ask gen AI unlimited questions, 24/7 and in their native language, without worrying that they are asking “stupid” questions or being bothersome to higher-ups.

In parallel, during the onboarding phase, managers must explain to the new hires how gen AI should be used in the enterprise setting. In fact, despite their proficiency, new hires are not familiar with the specific context of the enterprise. Training for these gen AI-savvy individuals should focus on responsible use, including ethics, policies, and operational guidelines. It is important for them to understand that using AI in a corporate environment necessitates adherence to specific rules that balance freedom with control. Unlike university settings where experimentation is often more unrestricted, corporations require compliance with established norms, which must be clearly explained since day one and consistently reinforced. Deutsche Telekom’s value-based compliance is a case in point. It moved away from traditional rules-based order to teach values to help all employees, particularly new hires, develop better judgment, preparing them better to deal with gray areas.

How companies can integrate Gen AI talent into the workflows

Integrating Gen Z’s AI fluency requires careful navigation. Their agile, experimentation-driven approach may clash with established workflows, leadership styles, and company culture, especially if colleagues are less familiar with gen AI. This challenge echoes past technological leaps, such as the introduction of the PC, email, and the Internet, which also required cultural and generational adjustments.

A proactive strategy is to immediately harness the expertise and experimental knowledge of new hires by appointing them as champions for gen AI-related projects and seeking their input, regardless of seniority or hierarchy. In the words of Kurt Matzler, professor of strategic management at Innsbruck University: “I have the privilege of interacting with these gen AI-ready students every day and learning from them. Executives must also develop a habit of fostering this learning, with a humble mindset.”

While younger generations bring AI readiness and tool deployment skills, more senior employees contribute contextual knowledge and sense-making abilities, qualities that inexperienced juniors may not have. Practices like reciprocal mentorship, like Airbnb’s “mentern” program, can accelerate knowledge transfer while deepening connections between people of different generations. This alliance is crucial for the responsible adoption of gen AI in business processes.

Consider the case of Andy, a senior executive in the finance department of a large technology company. He set up regular meetings with his team to experiment with gen AI models, assigning the coordination to a new hire who was more familiar with gen AI and more willing to experiment on the job. Through shared experiences and contextual experiments related to their roles, the team collaboratively explored and learned how to apply gen AI within established guardrails.

How companies can retain and grow GenAI talent

The rapid development of generative AI is changing the face of many traditional jobs. Companies must be prepared to update the required job skills, career paths, and promotion criteria to align with the new AI-first landscape. By doing so, candidates will clearly understand how their gen AI skills fit into their career progression. This necessitates revising job descriptions and competency models to be more in line with these evolving scenarios.

Additionally, gen AI will demand new tasks and new jobs that do not yet exist, creating new career opportunities. Take for example a career in marketing. Just as search engine optimization (SEO) became important during the era of web searching, a new field called LLM optimization (LLMO) is emerging. Employees who experiment with innovative gen AI techniques like this one and others will be highly sought after. Organizational leaders and must stay ahead of these trends and focus training and retention efforts in these areas.

. . .

These examples illustrate that the generation gap in adoption presents an opportunity to attract, integrate and retain gen AI-ready new hires. The dual goal is to keep them engaged and positive while helping other employees, including those with longer tenures, become familiar with gen AI and incorporate it into their workflows. It’s crucial for business leaders to recognize this now to prevent new hire frustration, reduce turnover, and facilitate a smooth transition to a new generation of gen AI-savvy managers without cultural clashes. This effort requires the involvement of the entire management team — not just HR. All managers must embrace this responsibility in their daily operations.

Copyright 2024 Harvard Business School Publishing Corporation. Distributed by The New York Times Syndicate.

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