Workera Watch

Workera has expanded its skills catalogue to assess whether employees can use specific AI tools, alongside the transferable skills they already measure. Its September product roundup also details three changes intended to make assessments more reliable and easier to configure.

Discussion spark: Should employers assess proficiency in the specific AI tools they choose, or focus on skills that can transfer when the tools change?

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Workera says it has added notices explaining AI use across its platform, including before assessments and during interactions with its AI agent. The change puts disclosure in front of people being assessed, as well as the administrators using the system, while EU transparency rules are now in effect.

Discussion spark: Should AI disclosure for hiring assessments have to explain how a result may affect a candidate, or is a clear notice that AI is involved enough?

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Workera’s survey of 1,000 employees at large US companies found that frequent AI use and access to AI-specific training have both grown, but workers still report obstacles to building skills. The useful distinction is between offering training and giving people the time and support to become capable.

Discussion spark: Should employers prioritise protected working time for AI practice, or spend first on more and better training materials?

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Workera says AI skills frameworks should keep durable capabilities in a stable core while letting tool-specific skills change or expire. Its proposed system uses agents to flag when skills descriptions drift, with human experts deciding what actually changes.

Discussion spark: Should organisations assess durable capabilities separately from tool-specific skills, or does splitting the framework make workforce skills harder to compare?

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Workera argues that finishing an AI course does not show whether someone can actually do the work. Its guidance is to assess the same people before and after training, using comparable tests rather than simply reusing the same questions, which can reward memory as much as learning.

That gives employers a more useful way to judge…

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Workera says its assessment of nearly 9,400 employees across pharmaceutical companies found a 14-point gap between foundational generative AI skills and responsible AI use. In a sector where AI decisions can touch clinical trials and patient care, that is a gap worth measuring, not merely hoping away.

Discussion spark: Should pharmaceutical companies have to demonstrate staff competence in responsible AI use before deploying AI in patient-affecting work, or is that too blunt a test?

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Workera says its August product updates let employers compare the same person’s capability before and after training, using assessment versions it says have been checked for equivalent difficulty. That is a more useful test of workforce learning than a completion tally, which can tell you who finished a course but not whether anyone learned anything.

Discussion spark: Should employers use assessment scores to make decisions about hiring and promotion, or keep them limited to measuring whether training works?

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Financial services firms are putting AI ethics and broader judgement alongside technical skills in workforce training, according to Workera. The company says employees reassessed in its programmes improved their average proficiency by 79 points on a 300-point scale, though the figures come from Workera and do not establish that training alone caused the gain.

Discussion spark: For AI in regulated finance, should workforce readiness be judged mainly by assessment scores, demonstrated performance on the job, or both?

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