Real-world AI: A field guide to AI use cases that deliver value now

AI capabilities are arriving in the digital workplace faster than most teams can evaluate them. Leadership is asking questions. Vendors are making promises. Employees are already using tools that no one has officially approved. The pressure to act is real – but so is the risk of acting on the wrong things. 

Real-world AI is designed to cut through the noise. Drawing on a DWG member survey, desk research and practitioner interviews, it maps the AI use case landscape with the clarity and honesty that digital workplace teams need in 2026. 

At its heart is a pattern library of 13 use cases organized across four tiers – Foundation, Emergent, Transformational and Horizon-defining. Each comes with a readiness level, characteristic failure points and real-world examples, so you can see at a glance where progress is fastest and where more groundwork is needed first. 

The report examines the enterprise Copilot reality – broad deployment, but adoption that remains shallow in most organizations – and the wider tool landscape, including the strategic choice between vendor-embedded AI and enterprise LLMs. A practical decision framework helps teams prioritize use cases based on content readiness, employee impact, governance and measurability. 

Case studies from Vodafone, Pearson, Lloyds Banking Group and a global consumer goods company show what genuine progress looks like – and what it takes to get there. 

The report’s central argument is that the governed content layer from which all enterprise AI draws its answers is the intranet team’s mandate to claim. The report offers four practical actions to start building towards it now, at whatever stage your organization has reached.