The business case for skills intelligence has never been stronger. Organizations today face a rapidly evolving talent landscape – one where AI is accelerating the pace of change and redefining what it means to be “ready for the future of work.” To stay competitive, companies need more than just learning content. They need trustworthy insights about the skills their people actually have and a system for closing the most critical gaps — not just tracking them.

Recent research underscores the urgency: organizations with a clear skills strategy are 3.4 times more likely to report high employee satisfaction and twice as likely to meet their business goals. Yet despite this clear upside, many companies still struggle to operationalize skills intelligence that’s accurate, scalable, and future-ready.

That’s exactly what Workera CEO Kian Katanforoosh and RedThread Research Co-Founder and Principal Analyst Dani Johnson set out to explore in a recent webinar. Together, they tackled the key challenges facing HR and L&D leaders today — from understanding the difference between skills inference and validation to building trust and transparency into skills systems powered by AI.

Here are four key takeaways from their conversation:

1.  AI isn’t a magic bullet. HR and L&D leaders need to be smarter about what AI can (and can’t) do.

As Johnson put it, “HR still isn’t always a sophisticated buyer of AI. We assume it’s a silver bullet.” But when it comes to AI in the skills ecosystem, not all capabilities are created equal. HR leaders need to push beyond polished demos to understand what’s scalable, secure, and useful in practice.

Katanforoosh explained that “building a prototype is easy, but a production system is extremely hard.” With content generation or skills inference, leaders need to ask the hard questions: What’s the underlying data? What does it mean for someone to “have” a skill? Is that conclusion based on real performance or just keyword recognition?

Critical thinking — from both people and systems — is essential. “You can't get the right answer out of AI unless you ask the right questions, and you have to understand the biases baked into the answers you're given,” Johnson noted.

1.  Future-ready talent tech stacks are built on capabilities, not just content.

A key theme throughout the conversation was the idea that technology decisions need to support long-term strategy — not just short-term convenience.

Katanforoosh advocated for thinking in terms of capabilities – like inferencing, validation, and knowledge generation – rather than simply choosing platforms with shiny interfaces. “If you’re building a skills-based organization, ask yourself: does this tool exist in that world, or is it going to be redundant in a few years?”

Many organizations have over-invested in aggregators but under-invested in validation tools that generate trustworthy data. 

Johnson agreed, adding that, “We're not going to find all the functionality in one vendor. Ecosystem thinking is critical.” She urged HR leaders to map out their full skills data architecture, including sources, system of record, and platform integrations.

One of the biggest risks? Buying in isolation. “The best leaders don’t position a new platform as a tech upgrade,” Katanforoosh said. “They frame it as a talent strategy.”

1.  Inference and validation are not created equal – but you need both.

One of the most common questions Workera hears is about inference versus validation. What’s the difference, do you need both, and how should their outcomes be treated?

Inference is the process of algorithmically estimating what skills someone may have, often based on past behaviors, content engagement, or job descriptions. Validation confirms what a person can demonstrably do, often via assessments, certifications, or performance-based evaluations.

“Inference is fast and broad,” said Katanforoosh. “It tells you what skills someone may have been exposed to.” That makes it useful for workforce planning and high-level strategy.

“Validation is slower, but deeper,” he continued. “It provides proof. It’s what you use when you’re placing someone on a high-stakes project or mapping out an upskilling path.”

Johnson emphasized the same. “The higher the fidelity of the data, the more validation is required,” she said. “That’s especially true when you’re making decisions that affect someone’s career, salary, or promotion potential.”

Workera sees most organizations benefiting from a strategic mix of both. “If I want to count how many people use Python, I infer,” Katanforoosh explained. “If I want to know who’s at an expert level and can be trusted with mission-critical work, I validate.”

1.  Trust and transparency are the linchpins of a skills-based organization.

“If you show people their skill profile in the HR or L&D system, most of them will be annoyed — it’s probably wrong,” Katanforoosh admitted. That’s why trust and transparency are so critical in building a system that both employees and leaders believe in.

It starts with giving employees the opportunity to validate their skills. “Inference alone often doesn’t involve the individual,” Katanforoosh said. “And that’s where trust breaks down.”

It also requires clear communication. Without transparency on how and why skills are assessed, even well-intentioned efforts can feel intrusive. Johnson highlighted how some organizations are drawing a hard line between how inferred skills data can and can’t be used. “They’re telling employees: this is just for development, not for performance. And they’re sticking to that.”

Leaders also need to position assessments correctly. “AI skills assessments are some of our most popular,” Katanforoosh said. “Why? Because employees see them as a growth opportunity. They feel the company is investing in them.”

That same positive framing is critical for more traditional or high-stakes skill validation efforts. “People are more defensive about what they’re supposed to know today,” Katanforoosh said. “But when you position it as future readiness, engagement goes way up.”

To hear more from their discussion, check out the full webinar recording. For more insights on how Workera helps HR and L&D leaders leverage AI to effectively and ethically assess skills, download our latest Responsible AI in Assessment: A Guide for Skill Development Leaders.