Our go-to authoring tool, Elucidat, has just released its annual report on Digital Learning. The report highlights trends, insights, and best practices for digital training.
Here at Apprendoo, we’ve compiled the report’s key takeaways to provide you with practical ideas and useful insights that you can apply to your learning strategies right away. 🚀
From experimentation to maturity in Digital Learning
For years, digital learning has been portrayed as an unexplored frontier with new tools, formats, use cases, and promises.
However, the tone shifts in Elucidat’s 2026 State of Digital Learning Report. The underlying message is clear: the era of experimentation for its own sake is over.
For L&D functions in 2026, the real challenge is no longer “What can be done?” but “What actually works?” Above all, the challenge is to build sustainable, useful, and measurable learning systems (find out what ROI is and how to correctly calculate it for your company).
A persistent gap between strategy and execution
The first striking finding concerns the perception of the role of digital learning.
95% of L&D leaders, who play a key role in corporate development, still consider digital learning a critical component of their 2026 strategy. However, only 14% feel fully prepared to make an impact, while 86% say they are not.
The gap between strategic importance and operational capability remains enormous and has not changed from last year.
The new priorities for L&D: quality, scale, and personalization
This tension is reflected in the priorities as well.
The most frequently cited priorities are improving quality and engagement (45%) and increasing scalability (18%), which we have discussed here.
However, new trends are emerging strongly:
- Personalization and adaptive learning (15%)
- Learning in the flow of work (13%)
- AI-assisted learning (9%)
In other words, producing content is no longer enough: we must design experiences that are more relevant, closer to real-world work, and useful for learners.
Growing obstacles: Budgets, Skills, and Resistance
Alongside these priorities, however, obstacles are also mounting.
The report highlights recurring issues, including budget constraints, resistance to change, technological limitations, skill gaps within the L&D team, and ethical and legal concerns related to AI usage.
This indicates that the sector is under pressure to continue delivering results amid rapidly changing models, tools, and expectations.
Training and retention: an increasingly strong connection
From the learners’ perspective, the picture is equally compelling.
The most significant finding is that 76% of employees say they are more likely to stay with a company that invests in their professional development.
Therefore, training is not just a performance driver: it is also a retention driver. Integrating upskilling and reskilling programs into corporate training is now necessary to ensure that employees grow with the company and feel valued.
How people really learn today
The way people want to learn is changing rapidly.
The report shows that learning still primarily takes place in the office or in dedicated spaces (81%) and on desktops (84%).
At the same time, available time is increasingly limited. A significant proportion of corporate training sessions are under 20 minutes, though about a quarter last 30 minutes or more.
This is an important point because it shows that the traditional long linear format doesn’t fit the actual rhythms of work.
The real issue: Content Quality and Relevance
When it comes to perceived quality, user feedback is clear.
44% want content that is more relevant and tailored to their role, and 24% prioritize the quality of the experience.
However, nearly half of learners believe that the quality of corporate digital learning has not improved in the past year.
More significantly: 41% rate AI-generated learning as barely adequate or poor.
L’AI, insomma, non sta risolvendo da sola il problema della qualità. Una delle opzioni è ricorrere alla Agentic AI e riuscire a chiudere il ciclo ADDIE con l’ausilio della tecnologia.
In short, AI alone is not solving the quality problem. One solution is to use Agentic AI to close the ADDIE cycle with the help of cutting-edge technology.
Increasingly autonomous learners (and outside of corporate systems)
Another key factor is employee autonomy:
62% have used AI tools, such as ChatGPT or Copilot, to support their learning in the last six months.
This indicates that people are building their own informal, self-directed learning paths, often outside of traditional corporate channels.
The real challenge for L&D is not to hinder this behavior but to guide it with rules, context, and quality.
AI in L&D: lots of experimentation, little real impact
The report also shows how the use of AI in Learning and Development functions is changing.
Currently, adoption is largely experimental:
- 45% are testing AI tools.
- 34% use them in limited areas.
- only 12% use them extensively
When asked how AI will truly make a difference, however, the most frequent response is “accelerating content creation” (75.5%), followed by analytics and reporting (50.5%), and adaptive/personalized learning paths (50.5%).
The point, however, is precisely this: the report urges us not to stop at productivity but to use AI to improve performance and decision quality.
The three key trends in digital learning in 2026
From these trends, three major ones for 2026 emerge.
The first is people and skills. The volatility of skills is increasing, so L&D must build transferable and lasting capabilities, not just technical knowledge.
The second trend is technology and infrastructure. Companies no longer operate with a single platform but with true learning ecosystems where integration and orchestration matter more than continuously adding new tools. If you need help with this, let’s get in touch!
The third trend is strategy and leadership. Data is increasingly less about capturing activities and more about driving decisions. Meanwhile, culture, managerial support, and psychological safety become multipliers of impact.
Real-World Examples: when digital learning really works
The case studies in the report point to the same conclusion.
For example, the Football Association built a more accessible and modular ecosystem for over 170,000 coaches, bringing learning to channels people already use, such as social media and online communities.
Benetton introduced a model featuring 15 minutes of “learning time” per week for 4,000 people in 14 languages, achieving a 60% increase in completion rates.
Finally, the National Trust transformed climate literacy, a complex topic, into an engaging experience for over 70,000 employees and volunteers. This demonstrates that training on complex topics can be practical, clear, and motivating.
What really works in Digital Learning today
The common thread is clear.
By 2026, digital learning will only be effective if it is brief, relevant, accessible, integrated into work, and supported by human connection.
That is why the report emphasizes concrete, practical actions, such as auditing existing data, establishing light-touch signals for skills, linking every metric to a decision, strengthening the capabilities of the L&D team, and investing in consulting skills, influence, and diagnostic ability.
Conclusion: the true role of L&D in 2026
The most important lesson, ultimately, is simple.
L&D in 2026 will not be judged by the amount of content produced, but by its ability to improve performance, support people, and ensure that learning truly happens within the workflow.
AI remains a powerful lever, but value is created only when technology, skills, culture, and leadership work in the same direction.
We hope this has been helpful, but if you’d like to learn more and read the full report, click here!
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