As the pace of artificial intelligence (AI) advances and use increases, the length of time a skill set remains relevant decreases. These related trends have profound effects on human resources (HR) groups, which have a two-fold AI-era talent management mandate.
First, HR leaders and practitioners must support their organization’s AI journey. This imperative requires HR groups to deconstruct jobs into skills and then reconstruct those roles in light of AI applications and activities. Second, HR teams, like every other organizational group, must continually identify ways to leverage rapidly evolving AI tools to enhance their effectiveness and efficiency.
Skills overhauls: Tear down, rebuild, repeat
“The average half-life of skills is now less than five years, and in some tech fields it’s as low as two and a half years,” according to a Harvard Business Review article published 18 months ago – prior to the widespread enterprise adoption of generative AI solutions and well before the current scramble to implement agentic AI. (Agentic AI tools enable autonomous task planning and reasoning support to achieve human-defined objectives while operating autonomously without continuous human intervention.)
It’s safe to assume that the half-life of advanced technology skill sets continues to condense. This means that more jobs need to be deconstructed into activity-based skills and then reconstituted in new formats as more skills are handed off to AI agents and tools that perform those activities more efficiently and effectively. Newly structured jobs will give AI-empowered employees additional bandwidth for more strategic, and often “more human,” activities, such as cultivating deeper relationships with key vendors and high-value customers.
While many organizations should consider shifting their talent management capabilities from a job-based architecture to a skills-based construct, there is no one-size-fits-all approach – and shifting may not be prudent in certain organizations. A skills-based structure works well for consulting firms, given the project-centric nature of the work and the need to understand skill sets in order to align the best team to address a client’s specific needs. But this structure may not work as well for role-based financial services organizations that often prioritize operational consistency to support risk management, and which depend on well-defined, specialized roles (e.g., risk analyst, compliance officer) dictated by regulatory requirements and certifications. That said, it may still be valuable to deconstruct and rebuild skill sets within specific roles: What skills do our highest-performing traders, client service professionals and risk managers demonstrate? Which of these activity-based skills can be performed by AI agents (e.g., those that are more repetitive than variable and/or those that are more independent than interactive)?
These types of questions require thoughtful considerations and answers that ultimately enhance strategic value. Just because a task can be automated doesn’t necessarily mean it should be.
Supporting the organization’s AI journey
As HR leaders and their teams support the enterprise AI strategy, they should consider the following actions:
- Frame AI strategy from the employee perspective: There are organizations that communicate their AI strategies and governance models to the workforce – and those that do so effectively. The latter group thinks and speaks through the employee lens by addressing questions such as What do you want me to do with AI? How will my AI-enhanced performance be evaluated? How will I benefit from these changes?
- Be realistic about external hiring: The World Economic Forum’s 2025 Future of Jobs Survey indicates that 70% of employers plan to address a pervasive skills gap (which is predominantly technological in nature) by hiring externally. Good luck with that at a time when demographic realities mean that far more humans are exiting the job market than entering it. Because many forms of AI skills will be difficult, and expensive, to hire as full-time employees, HR groups will need to emphasize other components of resourcing portfolios that include contractors, service partners, consulting firms and, increasingly, AI agents.
- Elevate learning and development: Given the tech-talent crunch, HR leaders, their C-suite colleagues and board members should treat the learning-and-development function as a strategic capability, one for which funding, oversight and execution have direct implications on organizational innovation and performance. As new AI tools enter organizations, employees will need to get up to speed on using them quickly, often with the aid of AI-powered training and upskilling tools.
- Address other demographic realities: HR practitioners should be sensitive to another demographic issue – the tendency for younger, digital-native employees to engage in AI-related training and upskilling more frequently than older generations. This disparity does not exist in a vast majority of organizations, but a newly released survey report from the London School of Economics and Protiviti suggests that it is prevalent enough to warrant attention.
- Differentiate pay and consider other rewards: As the AI skills competition intensifies, more companies will differentiate pay based on highly sought-after skills. Some salary-benchmarking firms already are recasting their analyses based on skills as opposed to job categories. Savvy HR leaders also look beyond compensation to cultivate and promote other rewards components, such as access to bleeding-edge tools, career growth opportunities, relationships with first-line managers and the quality of the organizational culture.
Conclusion: More human than human
HR’s own use of AI tools and external services partners that can assist with AI governance models, resourcing, the deployment of other leading practices and more will give leaders and practitioners more time for the heavier, more human lifts required to support the organization’s AI journey.
HR groups are deploying generative AI (GenAI), agentic AI and other advanced technology tools to improve employee self-service, leadership development, workforce risk assessments, personalized training and learning experiences, and a broad range of recruiting activities.
AI agents can also help with the deconstruction of existing jobs into collections of skills and activities that can then be reconfigured into AI-empowered roles. HR groups should prioritize this work. In an era defined by sweeping technological disruptions, HR groups have an opportunity to enhance organizational value greatly via their own form of creative destruction – and reconstruction.
This article originally appeared on Forbes Human Resources Council.
