The Josh Bersin 2026 study dropped a shockwave across corporate learning and development (L&D): 74% of companies report they can’t keep up with the demand for new enterprise AI skills — even as they spend over $400 billion annually on training, content libraries, and L&D tech. This gap isn’t about money; it’s about whether companies can actually build skill-ready workers fast enough to meet AI workforce readiness needs. 

The report highlights a deeper shift underway: traditional corporate training approaches are being outpaced by the pace of change. Dynamic information sharing — knowledge that flows in real time, embedded into work, rather than stored in static training modules — is emerging as the new model for learning. This trend has massive implications for talent development, corporate strategy, and the future of work. 

Below we unpack why the AI skills gap persists, how we might close it, and why partnerships in AI training programs — especially through models like the AI CERTs Authorized Training Partner (ATP) Program — are becoming essential. 

The Root of the Problem: Training vs. Real Learning 

Despite billions invested, L&D efforts have historically been rooted in “programs” — catalog courses, classroom sessions, and monolithic curriculum builds. But this approach struggles against: 

• Rapid skill obsolescence — half of a workforce’s skills may be outdated within two years according to some labor market research trends. 

• AI adoption creating entirely new job functions faster than traditional curriculum can update. 

• Worker feedback that training doesn’t align with real job demands. 

This creates an AI talent shortage at enterprise scale: companies want AI-capable people but can’t find them quickly. 

What’s replacing old training models is dynamic information sharing — breaking skills into micro, usable, real-time learning delivered at the moment of need (like just-in-time learning content directly embedded into workflows). This knowledge flow over training approach helps close gaps much faster than quarterly training cycles. 

Corporate AI Upskilling: Where We Stand 

In 2026, the debate has shifted from “Will AI impact jobs?” to “How fast will workers adapt?” Recent labor discussions indicate: 

• Nearly half of employers plan to increase hiring for AI-related roles and those who can work alongside AI tools. 

• Many workers worry their skills will quickly become obsolete — especially in technical and digital roles.  

Workforce transformation is under pressure not just from AI adoption challenges but from AI skills demand vs supply — global surveys continue to show demand far outstrips the available talent with validated skill credentials. 

This is where corporate AI upskilling must evolve: from awareness sessions and generic tutorials to role-based, certification-backed learning experiences that signal ability and readiness to employers. 

Shift from Traditional Training to Outcomes-Based Credentials 

One of the strongest signals in the market is that enterprises want validated competency, not just attendance. This has fueled a major trend in partnerships: 

Training providers and corporate learning teams are looking for trusted third-party credentials — not DIY course collections. 

That’s why organizations choose to become a partner with programs that supply role-based certifications. 

Become a partner with programs like the AI CERTs ATP Program and gain access to: 

• A suite of job-role-specific AI certifications accredited to ANSI ISO 17024 standards. 

• Ready-made content, exams, and delivery infrastructure so training teams can launch offerings without building fundamentals from scratch. 

• Learner pathways aligned to actual job roles — from technical AI engineer to business and leadership roles. 

This model contrasts sharply with generic “tool tutorials” and positions learning as measurable skill attainment rather than attendance. 

If your organization wants to deepen AI workforce readiness and offer enterprise clients meaningful credential pathways, consider the AI CERTs Authorized Training Partner (ATP) Program.  

Can Training Partnerships Mitigate Job Displacement Concerns? 

A major anxiety in the workforce is job displacement. Headlines about automation risks abound, and employees fear being replaced by machines. Yet numerous labor trends show AI creates new types of work — roles that blend human decision-making with AI-supported execution.  

Training partnerships that emphasize skill certification serve as economic safety nets in two ways: 

1. Validated Skill Evidence — Credentials provide proof that workers have mastered relevant competencies. 

2. Job Mobility — Certification-backed upskilling prepares workers for emerging functions, helping transition careers instead of displacing them. 

This is especially true when training pathways are integrated with corporate talent pipelines — not siloed off as standalone compliance courses. 

How Should Institutions and Companies Collaborate to Reskill Workers at Scale? 

Addressing the AI skills gap requires collective action: 

1. Universities and Enterprises Must Align Curricula with Real-World Skills 

Traditional academic programs often lag employer needs. Partnering with credential programs like the AI CERTs Authorized Academic Partner Program helps institutions embed industry-aligned AI certifications into degree tracks, improving employability outcomes and relevance.  

2. Corporate + Academic Pathways for Continuous Workforce Renewal 

Companies can work with both corporate L&D teams and academic partners to support lifelong learning. For example: 

• Offer employees access to stackable credentials while they work. 

• Build pathways where academic credits transfer to industry certificates. 

These collaborations deliver scale, consistency, and measurable workforce outcomes. 

3. Government and Public Policy Support 

National and regional workforce initiatives must include credentialing frameworks and public funding for upskilling. This spreads access and reduces inequality in skill access. 

The Future of AI Training: What the Data Says 

Bersin’s research — grounded in feedback from hundreds of CHROs — confirms a central truth: spending more on training doesn’t guarantee better skill readiness. (JOSH BERSIN) 

What does work? 

• Models built on continuous learning and feedback loops. 

• Credentials and assessments tied to observable workplace capabilities. 

• Partnerships that distribute the burden of curriculum creation while ensuring quality and relevance. 

For L&D leaders, this means rethinking annual training plans to focus on impact metrics — skill attainment, job performance changes, and internal mobility facilitated by credential achievement. 

Bridging the $400 billion AI skills gap requires a new paradigm of learning — one that values outcomes over input and validated competencies over completion certificates. Organizations that adopt continuous learning models, embed dynamic information sharing into workflows, and form strategic credential partnerships will make measurable progress in workforce transformation. 

If your organization is ready to go beyond generic tool tutorials and deliver real, role-based AI learning pathways, explore how to become an authorized training partner with the AI CERTs ATP Program. 

Explore Related Partner Opportunities: 

• AI CERTs Authorized Training Partner (ATP) Program — provider-focused certification partnership AI CERTs ATP Program 

• AI CERTs Authorized Academic Partner — for educational institutions planning credential programs Authorized Academic Partner Program 

• AI CERTs Association and Affiliate Partner Programs — network collaboration options AI CERTs Partner Programs 

Ready to deliver real AI workforce outcomes? Become a partner and join the next wave of corporate learning transformation. 

Recent Blogs