Skills Gap Is Looming
Employers are facing a widening AI skills gap. Recent research shows that two-thirds of business leaders would not hire a candidate without AI knowledge. The World Economic Forum projects that nearly four in ten core job skills will change by 2030, underscoring how quickly roles are evolving. Across industries, companies are realising that AI fluency—not just technical expertise—will define competitiveness in the next decade.
Massive Training Initiatives
Global reskilling efforts are underway. Microsoft’s recent training programs reached more than 23 million people in digital and AI skills in 2024. New certifications, such as entry-level AI literacy and generative AI foundations courses, are becoming standard professional credentials. At the same time, initiatives like the World Economic Forum’s “Reskilling Revolution” and government programs in Singapore and the EU are expanding access to AI education globally.
Corporate Programs Take Shape
Enterprises are now building their own “AI academies.” Toyota’s Software Academy, launched in 2025, will train over 10,000 employees in AI and data security across its group companies. Yet, despite strong demand, only around one in three workers say their employer provides adequate AI training—even though the majority want it. This disconnect has prompted companies to move fast, blending in-house training, bootcamps, and university partnerships to scale learning.
Learning by Doing
Successful upskilling programs follow the 70/20/10 model: 70% learning through work, 20% through mentoring, and 10% via formal instruction. IBM’s “New Collar” initiatives and Google’s AI crash courses exemplify this approach, combining coursework with real-world projects. Studies show that companies allowing employees to spend part of their time on applied learning see stronger results. Soft skills—adaptability, critical thinking, collaboration—remain as vital as technical know-how in an AI-driven workplace.
Case Examples of Reskilling at Scale
Microsoft’s global AI training push demonstrates how private-sector investment can drive workforce transformation. Toyota’s program shows how industry-specific learning can make AI accessible to manufacturing teams. Salesforce’s internal commitment—that every employee learns at least one AI tool—reflects executive-level ownership of the learning culture. Together, these models point to a future where every role is AI-augmented, not AI-replaced.
2023 | 2025 | |
|---|---|---|
% of firms providing AI training | 18% | 35% |
% of workers wanting AI training | 50% | 64% |
Executives requiring AI skills in hiring | 42% | 66% |
Share of job skills changing by 2030 | 44% | 39% |
The demand for AI skills is rising faster than company training capacity, widening the gap — but also creating opportunity for firms that move early.
Expert Perspectives
Global forecasts suggest that by 2030, tens of millions of new jobs will emerge, many requiring reskilling or upskilling. Consulting firms consistently cite the AI skills gap as the number-one barrier to enterprise transformation, advising leaders to treat training as a strategic investment. Some major corporations now spend over $100 million annually on reskilling, recognising that without capable people, the return on AI investment remains limited.
Takeaways for Business Leaders
Lead Learning from the Top
C-suite sponsorship matters. Executives should make AI literacy a universal expectation and protect time for employees to learn.
Invest in Multi-Channel Training
Combine e-learning, internal academies, and applied projects to create sustainable learning ecosystems. Encourage cross-functional exposure to data and automation initiatives.
Measure and Reward Progress
Track employee AI certifications, tool adoption, and innovation contributions. Link learning milestones to performance reviews and career advancement.
Partner with Educators
Collaborate with universities and online learning providers to align corporate curricula with emerging technologies and ensure a steady talent pipeline.
Build Human+AI Teams
Balance technical training with creativity, problem-solving, and leadership skills—areas where human strengths complement AI capabilities.