Every year brings predictions about revolutionary change in L&D. Most don’t materialise. Some do. The challenge is distinguishing signal from noise.

Here’s my honest assessment of what’s likely to actually change in 2026—and what will remain constant despite the predictions.

What Will Change

AI Becomes Infrastructure, Not Innovation

2025 was the year of AI experimentation in L&D. 2026 will be the year AI becomes ordinary infrastructure.

What this means:

• AI content generation will be standard practice, not cutting edge
• AI-powered personalisation will be expected, not exceptional
• AI coaching tools will be widely deployed
• Organisations without AI-enhanced learning will be clearly behind

Implications for L&D:

• AI fluency becomes table stakes for L&D professionals
• Differentiation shifts from “using AI” to “using AI well”
• Focus moves from AI adoption to AI optimisation
• Training providers like AI consultants Melbourne that offer structured progression from basic to advanced AI skills will see growing demand

Skills Become Central Currency

The shift from roles to skills accelerates through 2026.

What this means:

• More organisations adopt skills-based talent practices
• Skills taxonomies become essential infrastructure
• Skills matching for opportunities becomes routine
• Skills data quality becomes competitive differentiator

Implications for L&D:

• Skills architecture work intensifies
• Development programs must connect to skills frameworks
• Assessment shifts toward skills verification
• Career development becomes skills-path navigation

Learning Integrates with Work

The separation between “learning” and “work” continues dissolving.

What this means:

• Learning happens more in workflow, less in separate learning environments
• Performance support and learning blend together
• Just-in-time resources replace some formal training
• Learning is measured by work impact, not just completion

Implications for L&D:

• Design skills shift toward workflow integration
• Learning technology must connect with work tools
• Measurement emphasises application, not just acquisition
• L&D becomes more embedded in business operations

Analytics Mature

Learning analytics moves from experimental to operational.

What this means:

• More organisations can connect learning to business outcomes
• Predictive analytics for learning needs become feasible
• Skills gap analysis becomes more sophisticated
• Evidence-based L&D decisions become more common

Implications for L&D:

• Analytics capability becomes core L&D skill
• Data infrastructure investment increases
• Measurement expectations from leadership rise
• Programs without outcome evidence face scrutiny

Manager-Led Development Expands

Managers become more central to employee development.

What this means:

• Formal programs share development responsibility with managers
• Manager coaching skills become explicit requirement
• Tools support managers in development conversations
• L&D enables managers rather than replacing them

Implications for L&D:

• Manager enablement becomes major L&D focus
• Resources for managers increase
• Success depends on manager capability
• L&D influence requires manager partnership

What Stays the Same

Fundamentals Still Apply

Despite technological change, learning fundamentals remain:

What persists:

• Spaced practice still beats massed practice
• Active learning still beats passive consumption
• Feedback still accelerates development
• Application still determines transfer
• Motivation still predicts engagement

Implications for L&D:

• New technologies must serve enduring principles
• Beware of approaches that ignore learning science
• Fundamentals should guide innovation, not be abandoned for it

Relationships Still Matter

Technology doesn’t replace human connection:

What persists:

• Trust still enables learning
• Managers still shape development culture
• Peer relationships still influence growth
• Human facilitation still matters for complex development

Implications for L&D:

• Don’t over-automate what requires human connection
• Invest in facilitator and coach capability
• Build community alongside technology
• Balance efficiency with effectiveness

Change Remains Hard

Technology doesn’t make behaviour change easier:

What persists:

• People still resist change
• Habits are still difficult to modify
• Transfer still challenges training effectiveness
• Culture still trumps programs

Implications for L&D:

• Change management remains essential
• Don’t expect technology to solve human challenges
• Design for behaviour change, not just knowledge transfer
• Address environment alongside individual capability

Business Alignment Determines Value

L&D value still depends on business connection:

What persists:

• Programs disconnected from business needs still fail
• ROI questions still require answers
• Stakeholder relationships still determine influence
• Strategic alignment still separates high-performing L&D from mediocre

Implications for L&D:

• Business partnership skills remain essential
• Strategic positioning requires ongoing attention
• Measurement and communication still matter
• Technical L&D skill isn’t enough

Talent Remains Scarce

Competition for talent continues:

What persists:

• Skilled L&D professionals remain in demand
• Organisations compete for development capability
• Employee expectations for development remain high
• Development investment remains retention factor

Implications for L&D:

• Invest in L&D team development
• Build sustainable career paths
• Compete effectively for talent
• Address your own capability gaps

The Hype to Ignore

Some 2026 predictions won’t materialise:

“AI replaces L&D professionals.” AI changes what L&D professionals do. It doesn’t eliminate the need for human judgment, creativity, and relationship.

“VR/AR becomes mainstream for learning.” Extended reality remains niche—useful for specific applications, not general-purpose learning.

“Microlearning replaces everything.” Short content has its place, but complex development still requires extended engagement.

“Learning platforms consolidate to one winner.” The market remains fragmented. No single platform dominates.

“Employees become fully self-directed learners.” Most employees still need guidance and structure for development.

What L&D Professionals Should Do

Preparing for 2026:

Develop AI fluency. If you haven’t yet, make this urgent. You can’t lead AI-enhanced L&D without understanding AI yourself.

Build data skills. Analytics capability becomes more important every year. Invest in your ability to work with data.

Strengthen business partnership. The L&D professionals who thrive connect to business outcomes. Build those relationships and skills.

Stay current but not trendy. Follow developments, but don’t chase every innovation. Focus on what actually works.

Remember fundamentals. New technologies should serve learning principles, not replace them. Ground innovation in evidence.

Build adaptability. The specific changes of 2026 are uncertain. Capacity to adapt is the reliable response.

The Honest View

Predictions are uncertain. Some of what I’ve written here will prove wrong. Some will prove more right than expected.

What I’m confident about:

• AI integration will deepen
• Skills-based approaches will expand
• Analytics expectations will increase
• Manager-led development will grow
• Fundamentals will remain fundamental

The organisations that navigate 2026 well will be those that:

• Embrace genuine changes while ignoring hype
• Build on fundamentals while adopting innovation
• Invest in capability while managing costs
• Connect to business while maintaining L&D expertise

That’s been true every year. It will be true in 2026 too.

Prepare thoughtfully. Execute deliberately. Adapt as you learn.

That’s the path through another year of change.