AI is changing job descriptions faster than companies can update them. Talent leaders are instead turning to agile work design with people at the center.
Julie Jares
Director, Newsroom, Thought Leadership
Workday
Organizations developed traditional job descriptions for a business world that no longer exists. In a high-velocity AI economy, skill and task requirements shift faster than we can update any rigid document, and it’s turned the standard job description from a helpful hiring blueprint into a constraint holding talent teams back.
The scale of the transformation is staggering. LinkedIn’s 2025 Work Change Report projected that 70% of skills used in most jobs today will change by 2030, with AI the primary driver of the shift. Their 2026 report found skills like AI engineering and AI fluency are growing rapidly year-over-year in both small and large businesses.
This all renders the "fixed role" concept obsolete, requiring a move toward a more fluid, skills-based job architecture. Consequently, legacy workforce structures are failing to meet the moment. Fewer than 1 in 3 leaders believe that the skills within their organizations right now are the ones they need to succeed in the future. Only half say they even have a clear view of their workforce skills.
The first step to closing this gap is replacing traditional job descriptions with a dynamic approach to talent decisions that continuously aligns people, skills, and technology with business goals.
70% of skills used in most jobs today will change by 2030, with AI the primary driver of the shift.
Guide
When job descriptions include rigid requirements for specific degrees or work experience, they can discourage candidates who may be a strong fit for the role but come from slightly different backgrounds. That’s why skills—those candidates have now and their potential to develop new skills in the future—have become the top talent currency in the AI era.
This is only becoming more true as skill demands evolve faster. With AI now more prevalent than ever across the workforce and new skills emerging all the time, it’s impossible for traditional job descriptions to capture everything that qualifies a candidate for a role—let alone predict what that job will require in one, two, or five years.
Think about it: Just a few years ago, skills like prompt engineering, LLM training, and AI data model analysis weren’t even part of most organizations’ talent strategies. Today, they’re among the fastest-growing skills on the job market. The people already excelling in these areas are those who were willing to learn new things in their existing roles and take on new challenges.
Those are the people you want to attract to your workforce in the AI economy—but they’re also the ones you risk missing if you’re using outdated, rigid job descriptions. Education and experience still matter, but candidates best positioned to move your business forward are those with relevant skills and a proven ability to learn on the job.
So without job descriptions, how can companies define roles and recruit new talent? Role profiles move away from listing specific boxes a candidate must check (think “Masters Degree in Business, Finance, or Related Area”) but instead describe the kind of person you want to hire for a role (think “fast learner, proven innovator, effective collaborator”).
Can these kinds of descriptors still live on job descriptions? Sure. But the way your talent teams develop them internally has to change at a fundamental level. You no longer want to wait for a vacancy, pull up the old job description, update it, and hit post. Instead, you need a comprehensive, holistic, and real-time view of your current workforce and whether it’s driving your company toward its goals.
These key steps will help you lay the foundation for an agile, aligned, and intentional talent strategy built for an AI world.
Role profiles move away from listing boxes a candidate must check and instead describe the kind of person you want in a role.
Anchor roles in your organization with the specific outcomes they support and the skills needed to deliver those outcomes. For every new hire, instead of pulling up a templated job description, ask questions like:
Use those answers as a guide when you evaluate candidates. A startup founder, for example, may need a manager for their growing company who can lead a cross-functional team in a fast-paced environment that’s still scaling fast. To do that, they look for someone with proven skills in areas like cross-functional leadership, operational planning, adaptability, innovation, and AI workflow design.
Looking instead for a specific degree major (i.e. “Business Development”) or X number of years in a management role would be less likely to hone in right away on the role’s most critical indicators of potential success.
When talent teams don’t know the skills that exist in their organization, they can’t build skills-based role profiles intentionally. Take time to perform a skills audit. Collect information through internal skills assessments, manager input, and employee profiles in your HRIS system. Encourage people to update new skills as they develop them.
Use your system to maintain a clear view of workforce skills across the organization. That visibility should let you zoom out to analyze skills at the organizational level and zoom in to see them at the team, role, or individual level.
For example, when you need to fill a new role, you can first identify current employees who may already have the right skills to step into it. You can also spot the skills your teams are missing so you can hire or develop talent more strategically over time.
With AI the primary force pushing job descriptions out of modern hiring, it’s essential to make it a core part of talent decisions. As AI systems take on more analytical and execution-heavy work, the structure of many roles is shifting. Organizations need to define—at an enterprise level—how humans and AI operate together.
Start by establishing how AI is used across the organization right now. Document the kinds of work AI systems handle, how employees interact with AI systems, and when human decision-making and oversight is still required.
Once that structure is clear, reflect it in role design and skills-based hiring criteria. Employees should be hired not just for the work they do themselves but how they can manage and collaborate with AI systems as part of their daily work and adapt as those systems continue to evolve.
Most critical work in modern organizations already spans multiple teams. Product launches, customer onboarding, and major operational initiatives rarely sit inside a single department. Yet teams and hiring managers still design many roles around narrow functional boundaries.
Agile workforce design requires defining how work flows across teams and clarifying how roles contribute to shared outcomes. When designing roles, ask questions like:
Shared AI-enabled platforms make this coordination easier. Use them to give teams visibility into progress, streamline work handoffs, and reduce delays caused by siloed processes.
Agile workforce design depends on the ability to move and acquire talent quickly as priorities shift. Yet many organizations still default to external hiring whenever a new role opens.
Treat internal talent as the first place to look when filling open roles. Employees who already understand the organization’s systems, culture, and goals can often step into new responsibilities faster than external candidates. In fact, Workday research found internal hires are 81% more likely to be rated top performers than their externally hired counterparts.
Take advantage of your internal talent by making it easy for employees to see new opportunities in your organization. Internal talent marketplaces, project-based assignments, and skill-matching tools can all help employees expand their experience and explore new potential roles.
Organizations that move talent internally can adapt far more quickly than those relying primarily on competitive external hiring markets.
Internal hires are 81% more likely to be rated top performers than externally-hired peers.
Leaving legacy job descriptions behind in favor of modern work design means moving away from describing jobs and instead describing the type of people you want in your organization to achieve certain outcomes.
In an AI environment where conditions are constantly changing, leaders must support that mindset with an agile approach to talent management and hiring—AI-powered HR platforms, strong communication across business units, and hiring teams equipped with the knowledge they need to match talent to roles in a meaningful way.
In doing so, leaders can build more resilient organizations that are better prepared for change and better positioned to grow in the future.
Over half of business leaders are concerned about talent shortages—and only 32% are confident their organization has the skills needed for success. See how AI is transforming skills management in this report.
Guide
In the past decade HR has undergone a major evoluton from a supportive role to a strategic one. However, as this report finds, HR teams are more conservative on AI than finance and IT. That makes the potential competitive advantage even greater—learn more below.