AI news ·
Deploying AI without upskilling creates rework, data risks and leadership disconnect
Only 16% of workers receive AI training before using new tools, creating a 53-point readiness gap. This could cost the global economy $5.5 trillion by 2026.
A new Skillsoft report reveals a 53-point gap between leadership perceptions of AI readiness and employee reality, with 86 percent of workers using AI tools but only 24 percent feeling properly trained. This disconnect is driving rework, privacy risks, and communication breakdowns, threatening to cost the global economy up to $5.5 trillion in 2026 due to skills shortages.
The cost of untrained deployment
Skillsoft surveyed 2,000 full-time employees, managers, and executives between March and April 2026. The data shows only 16 percent of employees receive training before new AI tools are introduced, and fewer than one in ten feel their organization has clear AI governance. Mark Onisk, senior managing director of talent strategy at Skillsoft, said this lack of preparation creates immediate operational friction.
"AI adoption without applied training often creates rework because organisations deploy tools without ensuring employees understand how to use them effectively or responsibly," Onisk said. When AI processes disconnected data, it amplifies errors and produces outputs that require manual fixing.
Privacy risks and cold communication
Sophie Bretag, an HR and leadership specialist, warns that the risks extend beyond operational errors into data security and workplace culture. Employees inputting sensitive data without understanding the implications create privacy risks that could lead to serious breaches. Bretag also points to a degradation in workplace communication.
"I've seen, and been on the receiving end of, cut-and-paste AI-generated emails and they can land as cold, lacking in empathy and sometimes, quite rude," she said. HR leaders tasked with closing this readiness gap can explore resources for AI for Human Resources to build better governance frameworks.
Shifting from tools to skills
Moving past basic experimentation requires organizations to rethink workflows rather than just layering tools onto existing processes. Onisk emphasized that as agentic AI automates common tasks, human oversight becomes the critical factor in trusting outputs. He argued that the most durable skills are not technical, pointing to logic, reasoning, and judgment as perpetual capabilities.
Bretag advises people leaders to define the specific problems they want to solve and establish clear boundaries before rolling out any system. To build this foundational knowledge, HR teams can use the AI Learning Path for HR Managers to structure their upskilling initiatives and establish data governance protocols.
Why this matters for HR
HR departments must shift their focus from simply procuring AI tools to actively managing the human integration of those systems. The data shows that buying software is not enough; leaders must mandate training before deployment, establish strict boundaries, and prioritize durable skills. Without this structured approach, organizations will face compounding errors, security vulnerabilities, and a workforce that distrusts the very tools meant to help them.