As organisations accelerate artificial intelligence adoption, many are investing in AI literacy but falling short on preparing employees for long-term workforce transformation. A new report from The Conference Board finds that while AI use is becoming commonplace across the workplace, formal training, hands-on learning and large-scale reskilling strategies are not keeping pace—potentially limiting the business value organisations can realise from AI investments.
Artificial intelligence is changing how work is performed across industries, but most organisations remain focused on helping employees use AI in their current roles rather than preparing them for the new jobs and capabilities that AI will create. That is the central finding of a new workforce research report released by The Conference Board, which argues that enterprises risk widening the gap between AI adoption and workforce readiness if they fail to prioritise long-term reskilling.
The report, based on interviews with 35 enterprise leaders and a global survey of nearly 1,300 employees, suggests organisations have made measurable progress in introducing AI tools into daily work. However, many have yet to develop enterprise-wide strategies that equip employees for the broader workforce transformation expected as AI technologies mature.
According to the research, 55.1% of employees now use generative AI or AI agents on a weekly or daily basis. Despite this rapid adoption, only 33.3% have participated in employer-provided AI training during the previous six months, while 28.3% report that their organisation offers no AI training at all.
The findings highlight a growing disconnect between technology deployment and workforce development. As businesses embed AI into operations, employees are increasingly expected to use intelligent tools without receiving structured guidance on how those technologies should be applied effectively or responsibly.
The report also points to shortcomings in organisational support. Fewer than half of respondents believe they have sufficient time during working hours to develop AI skills, with 48% agreeing that their employer provides adequate learning time. A similar proportion said they have access to the tools, resources and technology needed to build AI capabilities.
Matt Rosenbaum, Principal Researcher for Human Capital at The Conference Board, said organisations have made progress in building AI awareness, but AI literacy alone is unlikely to deliver lasting business value.
Instead, he argues, organisations that achieve the greatest returns from AI will be those that enable employees to integrate AI into everyday workflows, continuously develop new capabilities and adapt as technology evolves.
The research suggests many current learning programmes remain focused on foundational AI skills, such as understanding generative AI and writing effective prompts. Far fewer organisations are investing in advanced capabilities, including managing AI agents, redesigning workflows around AI or applying AI to strategic business challenges.
This imbalance may become increasingly significant as AI evolves from productivity assistance to autonomous task execution. Emerging AI agents capable of completing multi-step business processes are expected to reshape job roles, requiring employees to supervise, orchestrate and collaborate with AI systems rather than simply use them as standalone tools.
The report argues that conventional corporate learning models are unlikely to meet these emerging demands. Instead, organisations should combine structured training with peer collaboration, hands-on experimentation and experiential learning. Enterprise leaders interviewed for the research consistently identified practical application—not classroom instruction alone—as the most effective way to build AI capability.
The Conference Board also recommends integrating AI learning across the entire employee lifecycle. Rather than limiting AI education to isolated training initiatives, organisations should embed AI capabilities into recruitment, onboarding, performance management, career development and leadership programmes. Linking workforce development directly to business strategy can help ensure AI investments translate into measurable organisational outcomes.
Another important finding concerns employee confidence. Workers who believe their organisation will help them adapt to AI are significantly more likely to expect AI to improve their jobs rather than threaten them. Marion Devine, Principal Researcher for Human Capital, Europe, said building that confidence requires organisations to provide employees with the time, support and opportunities needed to develop new capabilities as work continues to change.
The report also warns that most organisations remain focused on upskilling—helping employees perform existing jobs more effectively—rather than reskilling, which prepares workers to transition into entirely new roles created by AI-driven business transformation. Companies that delay large-scale reskilling until disruption becomes widespread may struggle to redeploy talent quickly enough to meet changing business needs.
These findings align with broader industry trends. Gartner has identified AI-enabled workforce transformation as a strategic priority for HR leaders, while McKinsey & Company estimates that millions of workers worldwide may need to change occupations or acquire substantially new skills over the coming decade as AI reshapes labour markets. The Conference Board’s research reinforces the growing consensus that technology investment alone will not determine AI success—organisational capability and workforce readiness will be equally important.
For Chief Human Resources Officers (CHROs), the report positions workforce transformation as a leadership challenge rather than simply a learning and development initiative. It recommends that HR leaders work alongside business executives, technology teams and learning specialists to build integrated AI strategies that connect skills development with business objectives, governance and organisational change.
As AI adoption accelerates, enterprises that invest in continuous learning, practical experience and long-term workforce planning are likely to be better positioned than those relying solely on short-term technology training. The research suggests that the competitive advantage of AI will increasingly depend not only on the sophistication of the technology itself but also on how effectively organisations prepare their people to work alongside it.
Market Landscape
Enterprise AI adoption is entering a new phase in which workforce capability is becoming as important as technology implementation. Organisations are moving beyond experimentation with generative AI toward broader deployment of AI agents, intelligent automation and workflow redesign, increasing demand for continuous learning and skills development.
At the same time, HR and learning leaders are shifting from traditional training programmes to integrated learning ecosystems that combine formal education, social collaboration and hands-on practice. As AI reshapes job roles, workforce reskilling is expected to become a strategic priority for organisations seeking long-term business resilience.
Top Insights
- The Conference Board found that AI adoption is outpacing workforce development, with more than half of employees regularly using AI but only one-third receiving formal employer-provided training.
- Most organisations continue to prioritise AI literacy and current-role upskilling rather than preparing employees for the broader reskilling required by AI-driven workforce transformation.
- Employees report limited access to dedicated learning time, practical experience and organisational support, highlighting barriers to developing advanced AI capabilities.
- The report recommends combining formal instruction with experiential and collaborative learning while integrating AI skills across the entire employee lifecycle.
- HR leaders are encouraged to align AI workforce development with business strategy to ensure technology investments translate into measurable organisational outcomes.
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