The New Age of Workforce Planning

Talent Implications of an Evolving Technology

Workforce planning in the midst of the AI revolution requires that CHROs both acquire new capabilities and lean on the existing expertise that helped them navigate other recent disruptions to the workplace.

Experts say HR executives need to stay current on how AI tools are evolving, collaborate with internal and external subject matter experts to understand how AI will reshape both technical and nontechnical job roles, and assess how accelerating use of the technology will impact headcount needs in short- and long-term scenarios.

The new reality is that the task of identifying which specific AI skills are needed for which job roles—and striking the right balance between AI use and human capital in the workforce—requires CHROs to develop a stronger partnership with both chief information officers (CIOs) and business leaders overseeing functions where AI use cases are expanding.

IT has historically “owned” technical and digital skills in organizations, but AI affects just as many nontechnical positions—such as those in marketing, customer service, finance, and HR—as it does technical ones (e.g., software engineers and cybersecurity specialists). Experts say that widespread impact should elevate the role of CHROs and chief learning officers in reskilling and recruiting talent for the AI age.

Adapting to ‘Agentic AI’

The challenge is compounded by the rapid evolution of AI, making workforce planning around the technology a moving target. The half-life of many AI skills is shrinking, meaning they are relevant for shorter periods of time. For example, industry analysts say a disruptive new “third wave” of AI is poised to go mainstream in 2025, impacting not only how CHROs provide workforce plans for the broader organization but also how they staff and develop their own HR functions. 

Called agentic AI, the technology features AI agents that are far more autonomous than today’s chatbots. They’ll have the ability to conduct multistep, complex operational processes in response to a single human request.

CHROs and talent leaders factoring AI into workforce planning will need new approaches, including more nimble learning strategies. But the fundamentals of the approach still apply, said Emily Rose McRae, a senior director analyst at Gartner who advises CHROs on the future of work. She said CHROs should ask the same questions of AI that they would of any new technology that’s broadly disrupting their organizations.

“How are we planning to use the technology to reach our strategic goals, and if we want to get the most from our technology investments, how should we change our job roles and workflows?” McRae said. “What doesn’t work is purchasing a license to access a new global AI technology without first having clear-cut use cases for it and failing to make adjustments to roles, workflows, and employee learning strategies.”

For example, McRae said she commonly hears this concern from many CHROs she advises: “They say employees aren’t using the generative AI tools the organization purchased, and they want to know how to develop their skills so they will,” she said. “In other cases, CHROs say workers are using the tools, but the organization isn’t getting the productivity improvements it expected.”

Assessing AI’s Role in Job Redesign

Some CHROs begin the workforce planning process by collaborating with functional business leaders and  IT executives to conduct a job task analysis that assesses where traditional AI, GenAI, or agentic AI tools might be introduced to enhance the productivity, efficiency, or performance of job roles across the organization—and how introducing AI would impact learning or recruiting needs.

McRae gave the example of an organization that implemented a GenAI tool to improve junior software engineers’ efficiency in creating first drafts of new computer code. Use of the technology resulted in a workflow change that now has senior software engineers reviewing those code drafts in a quality assurance role.

“You would want those junior engineers to receive training in prompt engineering for the specific GenAI tool they’re using,” McRae said. “You wouldn’t need the senior engineers to have the same training, but maybe some guidance or refresher training around quality assurance.”

Rather than opting to conduct a formal job task analysis, some CHROs are playing a different but equally valuable role in preparing their organizations for the impacts of AI, McRae said. 

“What these CHROs are doing is proactively providing guidance to business leaders on how to have conversations with their people about AI and helping them think through the talent implications of introducing the technology,” she said.

Jill Goldstein, global managing partner for talent transformation at IBM Consulting, said she encourages CHROs to engage with business leaders to help plan for the job redesign, workflow adjustments, or reskilling often needed to support AI implementations in their functions.

“For example, AI might be able to automate 40% to 50% of an accountant’s role today, but that accountant also may need to be reskilled to help train the digital assistant or bot taking over that work to function the way it needs to and to oversee its output,” Goldstein said. “CHROs can work proactively with CFOs to plan for that reskilling.”

Answering the Human Capital Question

One factor that can’t be overlooked when conducting AI-related workforce planning is the human capital that will still be needed even as AI takes over more of employees’ repetitive or lower-level job tasks. GenAI projects, for example, often require a level of human labor that surprises some business leaders.

 “There will always be a need for humans in the loop and, in many cases, a very skilled human conducting reviews, edits, and improvements of things like outputs from GenAI,” McRae said.

A 2024 SHRM study found 3 in 4 HR professionals agreed that advancements in AI will increase the importance of human intelligence in the workplace over the next five years. And a recent  study from Gartner also highlighted the need for ongoing human oversight and support for AI tools once they’re implemented.

In the Gartner study, executives of marketing technology companies were asked how much the introduction of GenAI had impacted their investments in both marketing labor and marketing technology. Only 10% said it had decreased their investment in labor.

“Survey respondents said AI wasn’t resulting in a need for less headcount, but it was providing advantages like enabling them to scale better,” McRae said.

Experts say workforce planning also should account for how AI will impact not only employee and team workflows but also workloads. McRae gave the example of an organization that recently implemented an AI tool to automate responses to the requests for proposal (RFPs) it receives. What the company didn’t consider in its initial planning was what the success of that AI tool might mean for the team responsible for onboarding and servicing new clients.

“If the AI led to a higher volume of new clients coming in, they might need fewer people writing responses to RFPs but more to conduct client service,” McRae said. “One solution was to consider asking some employees writing proposals to move into client service. Those currently writing responses also might have to conduct more review and quality assurance of the AI’s output.”

Making the ‘Build, Buy, or Borrow’ Decision

CHROs also face the decision of how to close AI skills gaps: with the “build” approach of reskilling existing employees, the “buy” tactic of recruiting new full-time talent, or the “borrow” strategy of hiring contract workers.

Because buying often proves more expensive and challenging—given the still-limited AI talent pools in many areas—most CHROs instead choose to equip their employees with new AI skills. Such reskilling, while not inexpensive, also can have the additional benefit of increasing workers’ loyalty and retention.

But exceptions remain for certain pivotal job roles. Pearson said her law firm opted for the “buy” approach in hiring a new director of AI innovation to guide the organization’s implementation of AI across functions.

“We brought in a thought leader who has deep AI skills within the legal world,” Pearson said. “He works alongside me in HR as we build training capabilities, helping to pinpoint exactly what AI skills we need and planning for our workforce of the future.”

Carissa Kilgour, a principal at Deloitte Consulting who leads the firm’s GenAI workforce strategies group, said part of that process should include examining job roles and activities that have a high degree of potential disruption from tools like GenAI. For example, a company with a need to recruit a large number of data analysts in the near term should weigh whether a “buy” or “borrow” strategy is the right approach.

“If that organization is adopting GenAI, the right move might be to hire more contingent workers instead of full-time labor because the AI use may result in less need for human analyst capability in the future,” Kilgour said. “If the technology and the skills needed for it are changing regularly and a company always wants top-of-the-market skills for it, they may want the flexibility of hiring best-in-class labor at the time they need it.”

Best Practices in AI Learning Strategies

Given that most CHROs opt for the “build” approach, experts say it’s vital they choose the right learning and development strategies for the workforce. But that path also can be strewn with pitfalls and missed opportunities.

An obvious problem is that some organizations provide little to no training or guidance to employees after introducing AI tools. A recent Gallup survey found that only 6% of employees feel very comfortable using AI in their roles and that between 2023 and 2024, the number of workers saying they felt very prepared to work with AI in their job roles dropped by six percentage points.

Because most organizational roles will require some degree of AI literacy, McRae suggested CHROs ensure that an annually updated “AI basics” training course is delivered to the entire workforce that describes how different types of AI work, the tools’ risks, how the company builds in quality assurance for AI outputs, and the organization’s philosophy on the technology’s use.

But unlike some experts, McRae recommended against training the general employee population in prompt engineering, the skill essential to mastering GenAI tools like ChatGPT, Google’s Gemini, or Microsoft Copilot.

“The learning science literature shows training is most effective when it’s delivered closest to when employees will use newly learned skills on the job,” McRae said. “I recommend to
CHROs they don’t teach prompt engineering until they have clear use cases and to avoid preparing employees generally for something they won’t use immediately because it will be a waste of resources. Teach prompt engineering only when GenAI becomes a regular part of employees’ workflows.”

McRae also suggested CHROs take a page from cybersecurity training that uses unannounced tests to assess whether employees can detect phishing attempts—efforts where hackers try to lure them
into clicking on malicious links in emails.

“I think every organization should develop a form of ‘information skepticism’ training around tools like GenAI,” McRae said. “GenAI models will ‘hallucinate’ and produce false or inaccurate information. You can’t fully train that out of them. We need our workforces to be able to identify signs of potential hallucination and know the next steps to take if they spot that problem. Creating phishing-like tests for GenAI would help companies check to see if employees are reporting hallucinations.”

Goldstein of IBM Consulting said CHROs also should encourage and support a learning culture where “failing fast” with AI tools and quickly applying lessons learned is celebrated.

“When it comes to AI, employees have to learn by doing and applying the skills in real-world scenarios,” Goldstein said. “That means giving them a safe space and enough time to play with AI tools. They need to be able to understand how the technology can be used to redefine or reshape their roles in a meaningful way.”

Pearson follows such a learning approach in her law firm, enabling employees to learn in a hands-on, engaging way from their peers and experienced AI users in the firm.

“We held an AI ‘prompt-a-thon’ learning event for our marketing, HR, and business development teams, and we’re continuing to roll that out for other teams,” Pearson said. “We create small teams within business units and say, ‘Here’s how the GenAI tool works, here’s how to create good prompts, go use the tool for an hour on one of biggest problems or challenges you can find in your function.’ We found when we use a team-based learning approach, people are less hesitant to use the technology and more likely to identify better use cases.”

As part of an AI learning strategy, Karen Consentino, chief people officer for Barge Design Solutions in Nashville, partnered with nearby Vanderbilt University to better understand how AI and large language models (LLMs) can be used to improve the productivity and efficiency of job roles across her company.

Consentino and her team also created a process through which engineering and architectural specialists can share their more advanced AI skills and transferable best practices with functions such as business services.

“It’s important for organizations to build that interconnectivity between work groups for learning around AI,” Consentino said. “It fosters a more collaborative dynamic. We also encourage and help our leadership regularly assess how AI can best be used in the day-to-day work of employees, and we have an innovation group that partners with our respective disciplines on how AI can be applied in their departments.”

Transparency Is Key to Success

Experts say strategic workforce planning tied to AI also needs to factor in one additional element that, if overlooked, can undermine the time and resources funneled into the exercise. Organizations need to ensure there is transparency from the executive team about how the company intends to deploy AI and its philosophy around use of the technology.

Despite research showing AI is more likely to augment than replace most jobs, employees still have fears the technology will place them in the ranks of the unemployed—or, short of that, may transform their jobs in ways that make the roles unrecognizable.

“Employees will only lean in to AI if they understand how it will be used within the context of their own jobs,” Goldstein said. “There needs to be a corporate commitment to transparency about why, when, and how AI will be used in the organization and how it may change the nature of jobs.” 

Dave Zielinski is a Minneapolis-based business journalist who covers the impact of emerging technologies on the workplace. He is the lead technology writer for SHRM’s HR Quarterly.