Why employees think AI is doing more harm than good

Employees face significant challenges with AI due to inadequate training and unequal access

AI has moved faster than most workplaces can keep up. Only 36% of employees say they have the training and resources needed to use AI effectively, a drop from the year before. That tells us something important: technology is moving ahead, but people are not keeping pace. Many businesses are deploying AI tools without preparing their workforces to use them confidently or productively.

The data also points to inequality in who gets access to training. Employees without four-year degrees are far less likely to receive AI instruction, and the gap is even wider for women in that group. This isn’t just an HR issue; it’s a strategic one. A business can’t scale AI effectively when large segments of its workforce are undertrained or excluded from development opportunities. That lack of inclusion limits innovation and reduces overall productivity across departments.

Executives need to view AI training as infrastructure, something core to a company’s foundation. Inclusive AI education programs can strengthen morale and improve long-term performance, especially in areas where labor shortages already exist. When every employee has the tools to adapt to emerging technologies, organizations can execute faster and innovate with less friction.

According to the survey data referenced, only 36% of employees currently have sufficient AI training, a decline compared to the previous year. This signals a need for leadership teams to invest in scalable, accessible learning systems. Businesses that take action now will build stronger teams and stay ahead as AI continues transforming every market.

The rapid integration of AI into job roles is intensifying the immediate need for upskilling

AI is not a distant concept anymore; it’s rewriting job roles across every industry. Three-quarters of early-career employees and 64% of experienced professionals report that AI is reshaping what they do daily. These numbers reflect a shift that’s already here. The vast majority of employees aren’t debating whether AI will impact their work; they’re living it.

Nearly half of all workers now say they need to learn new skills to keep up. That finding signals how deeply AI has penetrated the operational layer of most organizations. Only 7% believe their skill relevance has remained untouched by automation, proof of how quickly AI has changed expectations in workplaces built on traditional skill sets. The urgency is even sharper among workers of color, with 44% saying they must upskill within a year. For them, the pressure to adapt isn’t optional, it’s immediate.

For executives, this presents both a challenge and an opportunity. Workforce development must now move at the same speed as technological change. Companies that focus on continuous learning will build resilience into their operations. Structured upskilling programs can extend far beyond technical proficiency; they can shape more adaptable, agile teams capable of navigating future disruptions with confidence.

Data from JFF’s survey underlines this urgency: 29% of employees overall, and 44% of workers of color, say they need to acquire new skills within the next 12 months. Executive teams that recognize and act on this timeline, rather than delay, will gain a measurable advantage in innovation capacity and workforce stability.

Leaders now equate AI skills with fundamental communication skills

AI has become a foundational capability in the workplace. Many executives now view AI literacy as being as essential as writing or critical thinking. It’s no longer treated as a specialized area within data science or IT, it’s seen as a baseline competency for modern professionals. However, the execution gap between this vision and current workforce readiness remains wide.

About half of business leaders report substantial AI skill shortages within their organizations. This signals a clear disconnect between strategic ambition and capability on the ground. Companies are moving quickly to deploy AI tools, yet the internal expertise to support ongoing integration often lags. When core teams lack the foundational understanding of how to use and interpret AI outputs, progress slows, and productivity gains are lost.

Executives should treat this as a leadership challenge, not merely a technical one. Integrating AI fluency across teams requires sustained investment in training and a deliberate shift in hiring and role definition. Building internal AI capability creates alignment between leadership goals and workforce performance. It also opens the door to more informed decision-making as employees evolve from end-users of technology to contributors shaping its outcomes.

A February report by DataCamp highlights this issue clearly: around 50% of executives surveyed acknowledged “significant” AI skill gaps in their companies. For decision-makers, closing that gap is not optional. Embedding AI literacy into company culture will determine whether businesses can move from incremental process improvement to long-term competitive advantage.

AI-specific expertise has become globally the most challenging skill for employers to source

Across every major market, companies are finding that AI skills are the hardest to hire for. Demand for professionals with advanced AI capabilities, such as data analysis, automation design, and machine learning development, now exceeds that for traditional IT or engineering roles. This shift reflects the growing role AI plays in business strategy and operations. Skills once considered niche are now central to global competitiveness.

Executives are facing a shortage that limits how fast they can implement AI-driven solutions. Even organizations with strong technical foundations are struggling to find talent that can manage AI systems efficiently and ethically. The gap extends beyond software development, companies also need people who can interpret AI outputs, apply them to real business challenges, and ensure compliance with emerging regulations.

For leadership teams, this is a critical moment. Waiting for the market to fill these roles will slow progress. Instead, companies should prioritize internal development, building AI expertise through structured education and partnerships with universities, research institutions, or specialized training providers. Strengthening existing teams with AI learning paths ensures capability growth even when recruitment pipelines run thin.

According to a February report by ManpowerGroup, AI-related skills have officially overtaken IT and engineering as the most difficult to recruit globally. This finding underscores a long-term shift in demand. Executives who focus now on cultivating in-house AI proficiency will be better positioned to drive innovation, maintain agility, and sustain growth in a market where technical talent is becoming the ultimate constraint.

Key takeaways for decision-makers

• Close the AI training gap to unlock productivity: Only 36% of employees feel equipped to use AI effectively, and access is uneven. Leaders should invest in inclusive AI training programs to improve adoption, reduce inequality, and strengthen workforce performance.
• Treat upskilling as an immediate business priority: Three-quarters of employees see AI reshaping their roles, and 29% say they must learn new skills within a year. Executives should accelerate skill development initiatives to maintain agility and retain top talent.
• Build AI fluency as a core competency across teams: Half of leaders acknowledge significant AI skill gaps inside their organizations. Leadership should embed AI literacy into everyday roles to ensure strategy alignment and long-term competitiveness.
• Strengthen talent pipelines to meet global AI demand: AI skills now surpass IT and engineering as the hardest to hire. Executives should focus on developing internal AI expertise through structured learning and strategic partnerships to secure future-ready capabilities.