Assessing Your Talent Needs in the Age of AI

“Today’s CEOs are the final generation of executives leading exclusively human workforces,” Salesforce CEO Marc Benioff recently wrote in The Wall Street Journal. Recognizing this, some companies are thinking about talent in entirely new ways. For example, Moderna recently announced they’re merging their HR and IT departments under a chief people and digital technology officer, who is creating, redesigning, and eliminating roles based on what work will be performed by people and what will be done by technology. At a minimum, when considering the competencies you’ll need in the AI age, your organization must make some difficult strategic decisions: What work will be automated? How will humans and bots collaborate? How will you help employees gain the skills they and your organization need to compete? The first step—as in any talent analysis—is to clarify your company’s trajectory. Where is your business going, how fast, and how will AI fit into your strategy? Then, you can ensure your talent strategy is aligned with business needs. Here’s how to do that in the AI era. Recommendations Scenario plan for different levels of AI impact and different time horizons. AI is advancing so quickly that it’s difficult to predict what disruptions and changes an organization will face, and in what timeframe. In this context, scenario planning allows leaders to explore a number of possible shifts in business priorities, which can inform what skills their future workforce will need. Use AI to improve your scenario planning. Gen AI can rapidly ingest data from internal talent systems as well as industry and news reports, identifying trends and other external factors. It can then create a wide array of scenarios for your team to consider. Ask it to flesh out the most promising scenarios into detailed narratives—and to adjust variables with high uncertainty—so you can explore how your talent needs might change as a result. You can also ask gen AI to suggest drafts of talent strategies for each individual scenario. Prioritize near-term capability-building while preparing for longer-term transformation. One global airline used scenario planning to identify two paths to transformation. In the short term, it focused on deploying AI for predictive maintenance and customer service, requiring talent with data science and UX skills. In parallel, the airline explored an entirely new business model involving a new revenue stream from AI-powered travel planning across flights, hotels, and experiences. This required building deep expertise in AI product development and partnership management. This two-pronged approach guided both immediate workforce investments and longer-term capability building. Change the way you think about jobs. As AI adoption proceeds, roles will shift constantly as tasks are automated and new ones take strategic priority. While forward-thinking organizations already have been basing job descriptions around skills rather than preexisting roles, it’s now critical that all organizations adopt this mindset. Knowing what skills people have and what skills are needed for specific tasks allows organizational and talent leaders to adapt quickly, assembling project teams on the fly and focusing learning and development where it’s needed most. Map job tasks and associated skills. Begin with a granular view of work. Break down roles into tasks, and assess how each might evolve in the near future. Then identify the core skills needed to perform them. Conduct interviews with managers and employees to uncover hidden skills at play. (Often soft skills are less obvious.) Rethink job descriptions. If you’re still using traditional job descriptions centered around tasks to be done, it’s time to switch to a more flexible approach. Instead, job descriptions should focus on desired outcomes and the skills needed to achieve them. This makes it easier to hire a candidate—whether internal or external—based on what they can do, and not just what they’ve done in the past. For example, Unilever has been redefining roles as a collection of skills for some time. This has allowed the company to create flexible career pathways in which employees are considered for roles based on their skills rather than their current place in the organizational structure. Employees transition between a diverse set of assignments based on their skills, rather than being tied to fixed titles and roles. This offers employees flexibility and creates agility for the organization. Target your learning and development efforts. Once you know which skills are critical, you can deploy learning resources more effectively. AI can also assist with data-driven upskilling recommendations. Upskill your current workforce. LinkedIn estimates that by 2030, 70% of the skills for most jobs will change because of AI. Traditional one-size-fits-all seminars, workshops, and onboarding programs aren’t agile enough to accommodate this level of change. So, how can you get your employees the development they need? Make reskilling a responsibility of every manager. Middle management can sometimes resist reskilling efforts, because they worry about their team’s ability to keep up with their existing responsibilities, and they worry that other departments will poach their reskilled talent. But for these efforts to succeed you need the buy-in and investment of all people leaders. CVS holds managers responsible for designing and delivering reskilling programs for their teams, and these efforts are reviewed during performance assessments. Similarly, Amazon evaluates managers on how they’ve developed their team. Double down on human skills. In addition to AI capabilities, there are some universal human skills that are becoming ever more critical in an AI-driven world. Your upskilling efforts should include development of: Cognitive inference, or the ability to see connections between ideas, experiences, domains, people, and past and future. Collaboration and relationship building, or an array of emotional skills from empathy to conflict management. Curiosity, or the one human trait that AI has yet to successfully mimic. The most successful humans will continue to ask smart questions, be creative and innovate. Don’t give up on older workers. Employees over 50 are often disproportionately targeted for layoffs during periods of technological change because we tend to believe they can’t catch on as quickly to new technologies. But this simply isn’t true. And the elders of your organization are the ones with the institutional and industry knowledge and wisdom you need to carry the business into its next phase. Don’t leave them behind when handing out assignments for innovative initiatives. . . . The changes that AI brings will unquestionably take a toll on your workforce; there will be discomfort as jobs change dramatically. Leaders who acknowledge the difficulty of this transition and share what they do know—as opposed to expecting unbridled enthusiasm or keeping plans close to the vest—are more likely to earn the trust of their people. This sets the stage for stronger engagement, deeper loyalty, and better long-term results in a period that brings both great risk and great opportunity. Go Deeper Collaborative Intelligence: Humans and AI Are Joining Forces by H. James Wilson and Paul R. Daugherty HBR, July–August 2018 (16-minute read) Robots Need Us More Than We Need Them by H. James Wilson and Paul R. Daugherty HBR, March–April 2022 (17-minute read) Talent Management in the Age of AI by Ryan Roslansky HBR.org, December 4, 2023 (7-minute read) Reskilling in the Age of AI Jorge Tamayo, Leila Doumi, Sagar Goel, Orsolya Kovács-Ondrejkovic and Raffaella Sadun HBR, September–October 2023 (15-minute read) How to Reskill Your Workforce in the Age of AI Guest: Raffaella Sadun HBR’s The New World of Work, August 25, 2023 (18-minute read) Credits Expert advice courtesy of Francesca Campalani, EVP of consulting at Randstad Advisory, Paul Daugherty, chief innovation and technology officer, Accenture, Sandra Sucher, professor of management practice at Harvard Business School, John Winsor, executive fellow, Harvard Business School, and founder and chairman of digital staffing firm Open Assembly.

Assessing Your Talent Needs in the Age of AI

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