For decades, companies have approached learning and development (L&D) the same way: Assign courses by job title, hope for completion and check a box with a post-course quiz. This model may have scaled easily, but didn’t always deliver business impact, says one expert.
“Completion rates were abysmal,” says Kian Katanforoosh, CEO and founder of learning platform Workera, adjunct professor of deep learning at Stanford and author of his firm’s 2025 State of Skills Intelligence Report. “Even when courses were completed, the skills acquired didn’t move the needle on business priorities.”
He explains that training content often didn’t match employees’ skill levels or daily job needs. According to Katanforoosh, some HR leaders are moving away from a course-first approach to a skill-first, business-aligned strategy. He believes that companies must stop guessing what skills employees have and start accurately measuring them.
“People don’t need more content,” says Katanforoosh. “They need clarity on what matters, where they stand and how to get better.”
He’s not the only one with this outlook. For years, HR advisors have advocated for more advanced learning frameworks. Deloitte researchers say organizations must recognize when manual L&D curation becomes unsustainable. At that point, they say, automation, data-driven recommendations and reskilled learning teams are essential for navigating the new tech landscape.
Katanforoosh uses the term “skill intelligence” to describe a method of linking business outcomes to workforce capabilities. With this approach, companies assign training based on company priorities rather than job titles.
These priorities are then mapped to a skills framework, which helps measure employee capabilities. From there, organizations can recommend personalized learning experiences and track progress at the skill level, rather than just tracking course completions.
“L&D is no longer an event—it’s a flow,” Katanforoosh explains. “In a world changing this fast, you can’t afford to teach people what might be useful someday. You have to teach them what moves the needle today.”
Dynamic, verified workforce data
According to Workera’s data, only 11% of employees can accurately assess their skills. Most either overestimate or underestimate what they can do. Don’t rely only on worker analysis as a gold standard, says Katanforoosh, adding that conclusion-based information may be helpful but is not a full solution. “You need [skill] verification for L&D, internal mobility and performance conversations to be trustworthy.”
“Skill inference tells you where to look,” says Katanforoosh. “Skill verification tells you what’s real.” Katanforoosh says verified skills assessments fill that trust gap, offering HR leaders clear visibility into real capabilities and where the gaps actually are.
Mercer’s survey of over 14,400 C-suite executives, HR leaders and employees found rising demand for better insights to support internal mobility. Currently, one-third of companies in the study use tools like psychometrics, simulations, technical assessments and situational judgment tests to guide internal talent decisions.
However, Katanforoosh says that many HR teams still rely on traditional job descriptions and competency frameworks to guide training. He’s convinced that in today’s fast-changing environment, that approach falls short. “Static role descriptions are obsolete,” says Katanforoosh. “You need a dynamic, skills-first view of your workforce.”
He emphasizes that verified skill data is key to driving performance. As Mercer researchers note, understanding the work is only part of the productivity equation—insight into employees’ skills and capacity completes the picture. In fact, Mercer found that high-growth companies are 1.4 times more likely to assess talent throughout the employee lifecycle.
Skill assessment and verification enable smarter hiring, fairer promotions and help L&D teams demonstrate real ROI. “Learning isn’t the goal—capability is,” Katanforoosh says.
Read more | Rethinking L&D: An expert’s call to action for HR pros
Left out of AI training
One of the clearest insights from the State of Skills Intelligence Report—which surveyed 800 full-time professionals overseeing workforce development, skills strategy or L&D programs—is the urgency around AI. AI and machine learning are seen as the most important skills over the next three years, according to the report, yet only 14% of employees believe their organizations are fully on track to develop them.
Another problem is that employees feel left out: Only 10% say AI strategies are communicated well, according to the report. Also, if there is training, most of it seems to be generic, as only one in four employees received AI-specific training, according to the report.
“The demand for AI fluency is exploding,” Katanforoosh says. “And yet most organizations haven’t even defined what ‘AI-ready’ means.” The Workera report shows that organizations with a clearly defined AI strategy are consistently outperforming others. They’re three times more likely to say their training closes skill gaps, significantly more confident in their onboarding and 10 points ahead in getting new hires trained on AI within 90 days.
For HR leaders looking to act, the place to begin is with AI skills, says Katanforoosh. This area is already top of mind for executives and employees alike, and it cuts across every function. Most employees know they’re behind, he says, so what they need is a roadmap and a clear definition of “what ‘great’ looks like for each role, not just what ‘present’ looks like,” he says.
Within weeks, companies can define AI readiness by job role, assess current skills, benchmark against internal or industry standards and build personalized learning plans tied to real outcomes. From there, Katanforoosh says, HR leaders can replicate that same approach for other skill areas such as cybersecurity, data literacy, sustainability and leadership. “The template works everywhere,” he adds.
‘Turn learning into a superpower’
Katanforoosh outlines four phases that organizations move through as they adopt more flexible, skills-first learning systems:
One-size-fits-all: Everyone takes the same course, with progress measured by course completion.
Job-aligned learning: A pre-assessment places learners into different content tracks based on their skill level.
Dynamic curriculum: Pre-assessments identify individual needs, and content is automatically matched to fill skill gaps.
AI-mentored learning: An AI mentor uses baseline assessments to spot gaps, recommends personalized practice in real time and continuously tracks improvement. “This fourth phase is where true flexibility shines,” says Katanforoosh. “It’s scalable personalization, and it works.” He predicts that companies that turn learning into a superpower—not a checkbox—will come out ahead.
Most people want to gain better capabilities; they just don’t know what “better” means in their context, says Katanforoosh. Skill intelligence helps organizations define what excellence looks like for each role and measure where each person stands. Then, each can receive a clear path to progress.
The result is also good for people leaders: a more motivated workforce, better internal mobility and faster decision-making for HR leaders, says Katanforoosh.
