Workera analysis of over 800 participants finds a 42% average proficiency gain in 13 days and surfaces hidden capabilities across the workforce
PALO ALTO, Calif., June 18, 2026 /PRNewswire/ — Workera, the trusted skills data layer for the enterprise, today released findings from a leading global medical device manufacturer’s workforce transformation initiative, documenting measurable gains in learning velocity, proficiency, and capability maturity. The analysis, drawn from over 830 participants across structured upskilling programs, shows the company reached Workera’s highest performance tier, best-in-class learning velocity, while surfacing and developing previously hidden workforce capabilities at scale.
Medical device manufacturers face intensifying pressure to innovate faster while maintaining the safety and regulatory rigor that defines the sector. That demands a workforce that can move fluidly between established competencies and emerging technical capabilities, AI, cloud infrastructure, digital collaboration, without sacrificing precision or accountability. The challenge is widespread: the World Economic Forum’s Future of Jobs Report 2025 finds that 39% of workers’ core skills are expected to change by 2030, and 85% of employers plan to prioritize workforce upskilling by then. This manufacturer’s results show how verified capability measurement and personalized development can unlock both velocity and resilience.
“What this manufacturer achieved isn’t a faster training program, it’s a different operating speed for capability itself,” said Kian Katanforoosh, founder and CEO of Workera. “Their active participants moved from foundational to accomplished proficiency in under two months, roughly four times faster than typical industry rates. That kind of velocity doesn’t come from more content. It comes from verified measurement. When employees and leaders can see exactly where proficiency stands and where the gaps are, development stops being guesswork and starts being precise.”
The Transformation Results
Workera’s analysis examined verified capability across the company’s baseline proficiency, structured upskilling programs, and continuous learning pathways. The findings point to both strong execution and a repeatable model for enterprise skill transformation:
Best-in-class learning velocity: Active participants achieved a learning speed of +39 points per week, well above the industry average of 5–10 points per week. At that pace, employees moved from Beginning to Accomplished proficiency in under two months, placing the company in Workera’s highest tier: Level III (“Best-in-Class”).
Rapid, significant proficiency gains: Across all participants who took an initial assessment, studied, and reassessed, scores rose from an average of 168 to 239, a +42% improvement, in an average of just 13 days between assessments. The gains show that personalized development paths let employees focus on closing their specific skill gaps.
Program-level overachievement: While the platform-wide gain matched the +42% benchmark, the company’s core structured programs exceeded it:Core technical programs: +53% average score improvement per employee, in an average of 14 daysGlobal enterprise programs: +44% average score improvement per employee, in fewer than 15 daysCorrecting the self-assessment gap and reducing training waste: A persistent workforce challenge surfaced clearly in the data: employees routinely underestimate their own capabilities. Across cohorts, 78% of the broader employee population underrated their skills. By surfacing these hidden capabilities through objective measurement, the company avoided the redundant courses that drive most training waste, directing development only where it was actually needed and moving employees into high-value roles faster.
Full transformation in core power skills: The company drove Teamwork to Level 5 maturity (“Successful Transformation”), with 84% of assessed employees ranking as Accomplished and none remaining at the Beginning level. Foundational AI and leadership capabilities, including Generative AI Essentials (70% Accomplished) and Digital Leadership Fundamentals (67% Accomplished), crossed into Level 4 maturity (“Broad-Based Capability”), establishing a resilient, AI-ready cultural foundation.
Why This Matters for Medical Device Innovation
Medical device manufacturers operate under constraints many industries don’t: regulatory rigor, safety criticality, and the need to maintain established competencies while rapidly acquiring new ones. These results show those constraints and fast learning velocity are not in conflict.
Verified measurement enabled three outcomes:
Confidence in AI readiness: With 70% of the workforce at accomplished proficiency in Generative AI Essentials, the company can deploy AI-augmented workflows across product development, manufacturing, and operations, backed by decision-grade evidence that employees understand both capability and risk.
Precision in capability development: By measuring actual proficiency rather than course completion, the business identified who needed further development and who could move directly into high-impact roles, eliminating wasteful training cycles and shortening time-to-contribution.
Resilience through cultural alignment: Reaching Level 5 maturity in Teamwork across 84% of the workforce reflects something deeper than a metric, a culture where learning is embedded in how work happens, not layered on top of it. That foundation makes future capability transitions faster and more durable.
The Broader Implication
What this manufacturer achieved, moving from baseline to accomplished proficiency in a core capability in an average of 13 days, sets a new benchmark for enterprise upskilling. It challenges the assumption that workforce transformation is inherently slow, and shows that combining verified measurement, personalized development, and employee agency can accelerate learning velocity to four to five times industry norms without sacrificing quality or safety.
For medical device manufacturers balancing innovation speed with regulatory accountability, the insight is direct: the bottleneck to faster capability development isn’t employee capability. It’s clarity. When employees and leaders can see exactly what proficiency looks like and where gaps exist, development becomes efficient, measurable, and fast.
“The velocity here matters for every manufacturer and healthcare organization watching the AI transition,” Katanforoosh added. “Workforce transformation doesn’t have to be a 12-month program. It can be a two-month sprint, but only when you measure capability rigorously, personalize development precisely, and give employees clear proof of progress. In regulated industries especially, that combination is what makes speed and accountability compatible instead of opposed.”
To learn more about how Workera supports workforce transformation in medical device manufacturing and other regulated industries, visit workera.ai.
About Workera
Workera is the AI agent platform built to maximize human potential. Workera reads capabilities from the tools people already work in, verifies them continuously, and does so at scale. Our four purpose-built AI agents handle every talent decision: who to hire, who’s ready to move, where the gaps are, and how to close them. The newest, Ambient Coaching, surfaces skills intelligence in the flow of work. Trusted by the Fortune 100, Workera has been recognized by TIME’s Best EdTech Companies and World’s Top HRTech Companies in 2025 & 2026; the World Economic Forum’s Tech Pioneers; and Inc.’s 2025 Fastest Growing Companies. In 2024, Workera was named one of Fast Company’s Most Innovative Companies alongside Microsoft, Canva, and others leading the AI revolution. Learn more at workera.ai.
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SOURCE Workera
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