Recent research captures that half of all knowledge-workers are now using “shadow-AI” tools that their employer hasn’t approved, and a reported 46% even saying they would continue to even if those tools were banned. This article looks at why the problem is accelerating, where the exposure lies, and what moves technology leaders are making to channel shadow AI into governed AI.

From GitHub Copilot accelerating code delivery to AIOps predicting outages before they occur, software development teams are racing to embed AI across the SDLC. This article looks at mapping the opportunities and the risks in implementing AI across engineering delivery processes.

The journey from initial proof of concepts (PoCs) to realising tangible commercial value requires an engineering-focused approach. Here we discuss the common reasons for failure, and best practices for success in taking AI projects from PoC through to production.

Audacia shortlisted for AI Company of the Year and Technology Company of the Year at the British Data Awards 2025.

Successful software projects are rarely the result of chance. They emerge from a disciplined approach to understanding the problem, structuring requirements , and aligning teams. These same principles – clarity of vision, scope control and collaboration – are as essential to replacing a medieval Lego castle as they are to delivering a complex software system.

For many businesses, documents are the backbone of daily operations. Yet manual processing of these documents can be slow, error-prone, and often risky when it comes to handling sensitive data. This article explores how Azure Document Intelligence helps organisations automate document workflows, improving speed, accuracy, and compliance.

Without legacy constraints, greenfield projects allow teams to bake in modern practices, cloud-native architectures and a developer-first culture from day one. This article discusses how development teams can lay solid foundations when starting from scratch.

As data continuous to become the biggest operational challenge for organisations, here we discuss the question of whether teams should look to build their own data solutions in-house or, instead, leverage pre-built third-party data products.

This panel session brings together voices from data, engineering, delivery, and project management from MHRA and Audacia to share lessons from a successful GenAI implementation that is now helping to inform transparent AI in regulation around the world.

In this session, we will look at how AI is influencing software delivery today. Drawing on real team experience in delivering large-scale, enterprise software projects, the session will examine where these tools are genuinely helpful, where they introduce new risks, and what they mean for developer roles and engineering culture in the longer term.

Drawing on project experience delivering AI roadmaps with the Legal Ombudsman, this session will take a measured look at how to design and implement AI governance that works in the real world, with frameworks that are understood, adopted, and adaptable as systems evolve.

This session will showcase a case study on how an augmented team model has enabled sustained delivery, innovation, and continuity in a high-stakes environment, covering everything from architectural decisions to agile principles.