The world of talent and learning development is at an inflection point. Organizations are navigating tighter budgets, evolving skill demands and a rapidly shifting technology landscape — all at the same time. Based on Brandon Hall Group™ research and conversations with companies throughout 2025, here’s a comprehensive look at where things stand today and what to expect in the year ahead.
The Pressures Organizations Are Facing Right Now
If there’s one theme that cuts across virtually every talent challenge today, it’s time. Budget constraints consistently rank among the top organizational challenges and while financial pressures ebb and flow with economic conditions, the scarcity of time is a constant. As one analyst put it, “Money can’t buy you time in most places.” This reality shapes nearly every decision organizations make, especially when it comes to technology adoption.
From a broader talent management perspective, three challenges rise to the top:
- Financial constraints. Budget limitations remain the single biggest barrier to how organizations manage, develop and deploy their people. This is unlikely to ease in the near term, meaning L&D leaders must become even more skilled at doing more with less.
- Voluntary turnover. While the job market has shifted somewhat, retaining top talent — especially high performers — remains a strategic priority. The focus now is less on a red-hot labor market and more on keeping key contributors engaged and committed for the long haul.
- Upskilling and reskilling at scale. Skills have been a headline challenge for years and that hasn’t changed. The pace of change is accelerating and organizations are under pressure to continuously identify the skills they need, develop them in their workforce and do it fast enough to stay relevant.
The Hidden Skills Challenge
Here’s an interesting contradiction in the data: while skills are a top concern, two foundational activities (defining skills and competencies for roles and tying those to individual development plans) rank at the bottom of the list of perceived challenges. In other words, companies don’t feel particularly challenged by those things.
But that may not tell the full story.
In practice, building and maintaining a skills ontology is extraordinarily labor-intensive. Once created, there’s a natural temptation to “put it on a shelf” but skills frameworks are living documents that require continuous maintenance. More importantly, many organizations are still struggling to connect skills data to the actual work being done, the people doing it and the development opportunities available to them. That alignment of skills to people to work to development remains elusive for most.
It’s possible that organizations are underreporting how hard this really is.
Measuring Learning: Still a Work in Progress
Despite years of conversation about learning impact and ROI, most organizations are still measuring learning at the most basic levels, including completion rates, smile sheets and simple assessments. Very few have made meaningful progress toward measuring behavioral change (Kirkpatrick Level 3) or actual business results (Level 4), let alone calculating a true ROI.
This is a perennial challenge and it hasn’t gone away. Organizations continue to struggle with connecting what happens in a learning program to outcomes that matter to the business. Until that link is made more clearly, L&D will continue to fight for its seat at the strategic table.
The Technology Landscape: What Companies Are Adding
When it comes to learning technology, a few trends stand out:
- AR/VR and simulations are gaining traction as companies look to immersive tools that go beyond traditional eLearning.
- LearnOps platforms are growing in interest; organizations want tools to manage the business of learning, not just deliver content.
- Analytics and video remain high priorities as companies look to make more data-informed decisions and leverage richer media.
- LXPs still have a place, with about 30% of companies considering adding one, though the line between LXP and LMS continues to blur.
- The LMS sits at the bottom of the “adding” list, not because it’s irrelevant but because most organizations already have one (or several).
Notably absent from the list? A single line item for “artificial intelligence.” That’s not because AI isn’t important; it’s because AI isn’t one technology. It’s the engine powering all of the above.
How AI Is Actually Being Used in Talent and Learning
As of mid-to-late 2025, only about 11% of organizations said they weren’t using AI in any meaningful way. For everyone else, AI is showing up in a variety of forms:
- Content creation (61%) is the clear leader. AI is helping teams dramatically reduce the time it takes to develop learning content: not by replacing human judgment but by generating frameworks, outlines and drafts that people can then refine and polish.
- Support tools and chatbots are widely deployed, particularly for just-in-time performance support.
- Combining AI-powered tools to build custom platforms and workflows is how about 30% of companies are operating.
- Personalized learning is an active and growing use case, with AI helping surface the right content to the right learner at the right moment.
From a broader talent perspective, organizations are also exploring AI for:
- Improving employee engagement — Using AI-driven interactions to maintain connection and motivation.
- Automating processes — Stripping out time-consuming manual workflows so teams can focus on higher-value work.
- Personalizing development plans — Using AI to synthesize a wide range of data points into a more complete picture of each employee’s needs and growth opportunities.
- Optimizing talent allocation — Getting smarter about where to deploy people and when to invest in development.
- Predictive attrition analysis — Perhaps the most forward-looking use case, using AI to identify patterns across the organization that might signal flight risk, well before a manager would notice on their own.
On that last point, it’s worth noting: performance reviews alone are not sufficient predictors of future potential or attrition. The power of AI in this context lies in its ability to pull together data from across the organization, things humans wouldn’t think to correlate and surface patterns that would otherwise be invisible.
Predictions for 2026: A Sneak Peek
As highlighted in Brandon Hall Group’s HR Outlook 2026 book, several significant shifts are on the horizon:
- The Flexible Learning Ecosystem
Organizations will move away from centralized, monolithic learning platforms toward a more interconnected ecosystem of tools: specialized solutions for content creation, skills tracking and delivery, all working together. Blockchain-based credentialing may start to gain traction as a way to build a verifiable, portable digital record of an individual’s skills growth. AI agents will play a growing role in delivering learning directly within the flow of work.
- Cognitive Offload Curriculum
The idea of embedding learning directly into the workflow, via co-pilots and agents, will become more mainstream. Rather than pulling employees away from their work to “go learn something,” tools will identify learning moments in real time and deliver targeted support right where people are working. This makes “learning in the flow of work” less of an aspiration and more of an operational reality.
- Neural Learning Integration
Organizations will pay greater attention to how the brain actually learns and use those insights to inform the design and delivery of learning programs. Expect to see more science-backed approaches influence everything from content structure to pacing and reinforcement strategies.
- Learning as Personal Brand Currency
Learning won’t just be something the organization does to employees; it will increasingly become something employees actively build and own as part of their professional identity and career trajectory.
- Hyper-Personalized, Just-in-Time Learning
This is one of the most significant shifts on the near-term horizon. AI tools are finally making true personalization achievable: surfacing the right learning opportunity for the right person at the right moment, whether they’re in their email, their CRM or a project management tool. Proactive, micro-interventions will help employees address skill gaps in real time before small problems become larger ones.
- Mastery Guild Models
Organizations will experiment with community-based expertise models that formalize how knowledge is shared, developed and recognized across teams and departments.
- Predictive Learning for Employee Retention
Building on predictive attrition capabilities, organizations will start using AI-powered insights to proactively design and deploy development opportunities that address retention risk, turning learning into a retention strategy, not just a development one.
The Thread That Connects It All
Across every one of these predictions runs a common theme: seamlessness. The goal isn’t just more learning, or faster learning, or cheaper learning. It’s learning that feels like a natural, invisible part of how work gets done, as intuitive and integrated as the tools people already use every day.
We’ve been talking about “learning in the flow of work” for years. The difference now is that the tools to actually make it happen are finally here. The organizations that figure out how to put them together — intelligently, intentionally and with a relentless focus on outcomes — will be the ones that win the talent game in 2026 and beyond.
