Shaping the Future of Digital Learning Creation at Discover eLearning

As we move into a new year, our focus at Discover eLearning is clear: we want to play an active role in shaping a more open, transparent and empowering future for digital learning creation. Our recent entry into the Innovate UK Agentic AI Pioneers Prize 2025 reflects that commitment, as it centres on an idea designed to strengthen the way developers build and refine learning content in the years ahead.

Over the past few years, we have watched the wider eLearning tools landscape change rapidly as AI has become a headline feature across many authoring solutions. Yet the direction taken by much of the industry has raised concerns for us. Many platforms have introduced closed, proprietary AI features that promise speed but offer very little visibility into how outputs are created. Control, transparency and understanding of model behaviour have eroded, leading to homogenised content where tone, structure and decision-making often feel indistinguishable from one tool to another.

In parallel, pricing structures have created new barriers. Features that would genuinely benefit developers, such as improved translation workflows, frequently sit behind expensive add-ons. This increasingly divides the sector, giving a clear advantage to organisations with significant budgets while limiting access for everyone else. For a discipline built on creativity, problem-solving and experimentation, that divide is troubling.

There has been promising work in newer AI-assisted content creation platforms, but even these often rely on token-based systems and proprietary pipelines. Anyone with hands-on experience in AI development knows that meaningful results come from iterative refinement. Token limits make such iterative work impractical, ultimately reducing the quality and uniqueness of the outcomes.

Our direction at Discover eLearning is deliberately different. We want to support a future where developers retain full control over how AI contributes to their work. Our proposal for the Innovate UK Pioneers Prize sets out a vision for a new publishing platform built from the ground up around open, agentic workflows. In this model, creators can connect to the AI services they choose, make use of their own or third-party models, and even integrate local LLM inference when needed. They will be able to design their own automation chains and build sophisticated agentic behaviours through tools such as n8n.

The aim is not to replace creative thinking but to make AI a transparent, configurable and genuinely helpful component of the design process. This approach enables new opportunities: adaptive learning driven by meaningful data, rapid prototyping informed by clear logic, and automated refinement routines that enhance a developer’s intention rather than override it. It supports the craft of digital learning design rather than diminishing it.

Whatever the outcome of the competition, the development journey starts now. We plan to move quickly with a proof-of-concept build, test ideas with our clients, and document the experiments and insights that emerge as we explore what an agentic, problem-solving mindset can unlock for the sector.

Alongside this work, we are also developing the next evolution of the eLearning Magic Toolkit. After several years of pushing the boundaries of what is possible when integrating Articulate Storyline 360 with generative AI, our aim is to take the concept further with a new app-based system that will work across all SCORM-compliant LMS platforms. This will give far more developers the opportunity to bring advanced generative AI capability into their own learning experiences, with flexibility and security at its core.

As we step into the new year, our priority is simple: to ensure that AI becomes a tool that strengthens the creative power of digital learning professionals, rather than diminishing it. We look forward to sharing our progress and inviting others to explore what is possible when open, agentic workflows become central to the design process.