New research from The Conference Board raises an important question: Are employers helping workers prepare for the future of work, or simply teaching them to use today’s technology?
Artificial intelligence is changing the workplace faster than many organizations can prepare their employees. Companies are investing in AI training, workers are experimenting with new tools, and employers are encouraging greater productivity. But an important question is emerging: Are these efforts preparing workers for the jobs they will perform in the future?
New research from The Conference Board suggests that many organizations may be concentrating on the wrong part of the challenge.
In its 2026 report, Skilling for AI: Critical Factors for Navigating AI Disruption, The Conference Board found that employers are primarily helping workers use AI in their current positions rather than preparing them for the more substantial changes in jobs, responsibilities, and skills that AI may bring.
For workforce development professionals, this distinction deserves attention. Learning to use AI and preparing for an AI-transformed workplace are related, but they are not the same thing.
Workers Are Moving Faster Than Training Programs
The Conference Board’s research, based on interviews with 35 enterprise leaders and a global survey of nearly 1,300 workers, reveals a significant gap between AI adoption and employer-supported learning.
According to the findings:
- 55% of workers use generative AI or AI agents daily or weekly.
- 33% have participated in employer-provided AI training during the previous six months.
- 28% report that their organizations provide no AI training.
- Only 48% believe their employers provide sufficient time during working hours to develop AI skills.
These findings suggest that employees are often learning to use AI independently, experimenting with tools as they become available rather than following a coordinated workforce development strategy.
This experimentation can be valuable. Workers frequently discover practical applications before their organizations develop formal programs.
However, individual experimentation does not necessarily prepare an organization for broader workforce transformation.
The Difference Between Upskilling and Preparing for Change
Much of today’s AI training concentrates on helping employees perform familiar tasks more efficiently.
Workers learn to draft documents, summarize information, analyze data, create presentations, and automate routine activities. These capabilities can generate meaningful improvements in productivity.
But what happens when AI changes the work itself?
Consider an administrative employee who learns to use AI to prepare reports. That represents an improvement in performing an existing responsibility.
Now consider an organization where AI eventually handles most routine reporting. The employee’s future value may depend less on preparing reports and more on interpreting results, identifying problems, exercising judgment, and recommending decisions.
The distinction is important.
Upskilling helps workers perform their current jobs better. Reskilling prepares them to perform substantially different work.
The Conference Board finds that many organizations are emphasizing the first while giving considerably less attention to the second.
This could leave employers with workers who understand today’s AI tools but are unprepared for tomorrow’s responsibilities.
A Different Way to Think About Workforce Planning
Traditional workforce development often begins by identifying occupations expected to grow and determining the skills people will need to enter those occupations.
Artificial intelligence complicates that approach.
An occupation may retain its familiar title while the responsibilities within it change substantially. Some tasks may be automated, others may become more important, and entirely new responsibilities may emerge.
A customer service representative, for example, may spend less time answering routine questions and more time resolving complicated problems that require empathy, judgment, and specialized knowledge.
An accounting professional may devote less time to routine data processing and more time investigating discrepancies, interpreting financial information, and advising clients.
These are illustrative possibilities rather than established predictions about particular occupations. Nevertheless, they demonstrate why workforce planning increasingly needs to examine the tasks within jobs, not simply job titles.
For workforce professionals, the important question may no longer be only which occupations are growing.
It may also be: Which responsibilities within existing occupations are changing, and what new capabilities will workers need as a result?
Why Traditional Training May Not Be Enough
Another important finding from The Conference Board concerns how employees develop AI capabilities.
The research suggests that formal instruction alone is insufficient. Effective AI learning increasingly combines structured training, collaboration with colleagues, and practical experimentation.
This makes sense when considering the speed at which AI technology is developing.
A course that explains how to operate a particular tool may become outdated relatively quickly. More durable capabilities involve understanding how to evaluate AI output, integrate technology into work processes, recognize limitations, and apply human judgment.
Workers need opportunities to experiment with AI while performing real tasks, preferably with guidance and feedback.
Employers also need to give employees sufficient time and access to technology to develop these capabilities.
The research points toward a broader lesson: AI workforce development should be integrated into daily work rather than treated exclusively as a separate training activity.
An Emerging Opportunity for Workforce Development Organizations
The findings also raise questions about the future role of workforce boards, professional associations, community colleges, and other workforce development organizations.
Many workforce programs are structured around helping individuals acquire skills for existing occupations or connecting jobseekers with available positions.
Those responsibilities remain important. However, AI may create another need: helping employers and workers anticipate how jobs are changing before large-scale displacement occurs.
This could involve working with employers to identify tasks that are being automated, determining which employee capabilities will become more valuable, and developing strategies to help existing workers transition into revised or emerging responsibilities.
Small and midsized employers may face particular challenges because they often lack dedicated workforce planning and organizational development resources.
Workforce organizations could help fill that gap by convening employers, sharing information about emerging changes, and connecting businesses with relevant learning resources.
There is also an opportunity to help employers distinguish between purchasing AI training and developing an actual workforce adaptation strategy.
These are different investments, and they may produce very different results.
The Questions Workforce Professionals Should Be Asking
The Conference Board research provides an opportunity to reconsider several assumptions about workforce preparation.
Rather than beginning with the question of what AI courses workers need, workforce professionals might begin with a different set of questions:
- Which tasks are employers already changing or eliminating through AI?
- What new responsibilities are emerging as AI assumes more routine work?
- Which workers are most likely to need substantial reskilling rather than incremental upskilling?
- How can employers provide practical learning opportunities as work changes?
- What evidence would demonstrate that AI training is improving organizational performance or employee adaptability?
Answering these questions requires ongoing conversations with employers, observation of changing work practices, and a willingness to adjust training strategies as new information becomes available.
It also requires recognizing that the effects of AI will differ across occupations, industries, and individual workplaces.
Preparing for Jobs That May Not Yet Be Clearly Defined
Perhaps the most important implication of the research is that workforce development cannot rely entirely on predicting which specific AI-related jobs will emerge.
Many future responsibilities will evolve gradually as employers discover new ways to organize work.
Consequently, the ability to adapt may become as important as proficiency with any particular technology.
Workers will need technical knowledge, but they will also need critical thinking, problem-solving, sound judgment, and the capacity to learn continuously.
Employers will need to reconsider job design, career pathways, and how they recognize and reward employees who develop new capabilities.
And workforce development organizations may need to shift some attention from preparing people for clearly defined occupations toward helping them navigate occupations that are continually changing.
The Conference Board’s findings do not suggest that current AI training is wasted. Learning to use today’s technology is an important starting point.
But it is only a starting point.
The larger workforce development challenge is not simply teaching people to use artificial intelligence. It is helping people remain valuable, productive, and adaptable as artificial intelligence changes the nature of work.
That distinction may help determine which organizations and workers are best prepared for the next stage of technological change.
Source: The Conference Board, Skilling for AI: Critical Factors for Navigating AI Disruption (June 8, 2026), and accompanying news release, Report: Most Organizations Are Preparing Workers for Today’s AI, Not Tomorrow’s Jobs (July 28, 2026).