GEFIE 1c – AI Accelerator Day with Glanua

Client: Glanua 

Event: GEFIE 1c – AI Accelerator Day 

Industry: Environmental Services 

Date: 31 March 2026 

Consultant: Niels Footman, Samiul Hoque

Building Practical AI Literacy Across Environmental Services Teams in London

Executive Summary  Glanua engaged Dixon AI to deliver a GEFIE 1c – AI Accelerator Day in London, focused on establishing a shared foundation of AI understanding across the organisation. The session brought together participants to explore, test and apply AI tools in a structured, hands-on environment. Anchored in the AI Transformation Playbook, the event created a clear step-change in practical AI literacy, giving teams the confidence to begin using AI within their day-to-day workflows.

Business Context  Operating within the environmental services sector, Glanua works in a context shaped by regulatory requirements, operational complexity and the need for efficient delivery across projects. At this stage in the AI Transformation Playbook, the organisation was in the early phase of building organisational AI literacy. The priority was to create a consistent baseline of understanding across teams, enabling more informed exploration and reducing reliance on fragmented, informal learning.

Objectives of the Event

• Establish a shared understanding of core AI concepts across participants

• Provide hands-on experience with a range of AI tools

• Build confidence in applying AI to everyday tasks

• Create a common language to support future collaboration and learning
  

What Happened During the Event  The GEFIE 1c session was delivered as a full-day, in-person workshop with a strong emphasis on participation and practical use. Attendees worked directly with a range of AI tools, guided through structured exercises designed to demonstrate how these systems can support real work scenarios.

Participants created accounts, tested different platforms and explored how AI could assist with tasks such as drafting, summarisation and problem-solving. The session moved quickly from demonstration to application, ensuring that learning remained grounded in direct experience rather than theory.

Throughout the day, participants shared observations and discussed how the tools could be applied within their own roles. This created a collaborative learning environment where insights were exchanged across functions, helping to build a more connected understanding of AI across the group.

By the end of the session, each participant had working access to multiple tools and a clearer sense of how to begin using them in practice.

Key Insights and Takeaways  A consistent theme was the speed at which understanding develops once people begin using the tools directly. Initial uncertainty tends to reduce quickly when participants move from observation to application.

The session also highlighted the importance of shared language. When individuals understand core concepts such as models, prompts and different types of AI systems, conversations become more productive and less dependent on individual interpretation.

Another observation was that early value often comes from small, practical applications rather than large-scale initiatives. Simple use cases within existing workflows provide a more reliable starting point for building confidence and momentum.

Impact  The immediate outcome of the session was a clear uplift in confidence and capability across participants. Individuals left with the ability to engage with AI tools independently and a practical understanding of where these tools can support their work.

At an organisational level, the event established a consistent baseline of AI literacy. This reduces variation in understanding across teams and creates a stronger foundation for future stages of the AI Transformation Playbook.

The shared experience also contributed to increased openness around AI usage, making it easier for teams to continue learning and experimenting after the event.

What Happens Next  Following GEFIE 1c, the next step is continued exploration and practice. Participants are expected to apply what they have learned within their roles, building familiarity through regular use.

As confidence grows, selected individuals or teams may progress to more structured experimentation, where AI is applied to specific workflows or challenges. This progression aligns with the next stages of the AI Transformation Playbook, where learning begins to translate into defined use cases and measurable outcomes.

Maintaining momentum will depend on continued access to tools, opportunities for collaboration and reinforcement of the shared language established during the session.

Closing Insight  Establishing AI literacy is less about transferring knowledge and more about enabling experience. When people have the opportunity to test tools directly, understanding develops quickly and confidence follows.

The GEFIE 1c session demonstrates how a single, well-structured intervention can create that initial shift, turning AI from an abstract concept into something practical and usable within everyday work.