Webinar Description
Key Takeaways
- Explores the relationship between data quality and effective AI deployment in Microsoft 365 environments
- Addresses storage optimisation, retention policies and lifecycle management as interconnected disciplines
- Designed for IT leaders, data governance professionals and Microsoft 365 administrators
- Examines the gap between theoretical AI readiness and practical implementation challenges
- Hosted by Cloud Essentials as a virtual panel discussion
Introduction
The webinar “Clean Data. Smarter AI. Lower Costs.” examines how organisations can prepare their Microsoft 365 environments for AI adoption while managing storage expenditure. Aimed at IT leaders and data governance professionals, the session addresses a challenge that has become increasingly pressing as enterprises deploy tools such as Microsoft Copilot: the quality of underlying data directly determines the value organisations can extract from AI investments. With many businesses sitting on years of duplicate, outdated and redundant information, the timing reflects a broader industry reckoning with the prerequisites for successful AI enablement.
About This Event
Hosted by Cloud Essentials, this virtual panel discussion brings together perspectives on enterprise information management within Microsoft 365. The interactive format allows participants to engage with the discussion as it unfolds, moving beyond passive presentation into practical dialogue about implementation challenges and solutions.
Data Quality as the Foundation for AI Effectiveness
A central theme of the webinar is the distinction between being AI-ready in theory and achieving readiness in practice. Many organisations have deployed Microsoft 365 and may have access to Copilot, yet find that AI outputs fall short of expectations. The underlying cause frequently traces back to data quality issues that predate any AI initiative.
When AI tools query corporate data repositories, they work with whatever information exists. If that information includes outdated project files, duplicate documents across multiple locations, or content that should have been archived years ago, the AI will surface and synthesise this material alongside current, accurate data. The result is diminished trust in AI outputs and reduced adoption among users who encounter inconsistent or irrelevant results.
The session positions data governance not as a compliance exercise but as a strategic enabler. Organisations that invest in cleaning and organising their information assets before or alongside AI deployment tend to see faster time to value and stronger user confidence in AI-assisted workflows.
Storage Optimisation and Lifecycle Management
Beyond AI effectiveness, the webinar addresses the financial dimension of unmanaged data growth. Microsoft 365 storage costs accumulate as organisations retain information without clear policies governing what should be kept, archived or deleted. Retention policies and lifecycle management provide mechanisms to automate these decisions, reducing both storage expenditure and the volume of low-value content that AI tools must process.
The discussion frames storage optimisation, retention policies and lifecycle management as complementary disciplines rather than separate initiatives. When implemented together, they create a sustainable approach to information management that addresses immediate cost concerns while establishing the conditions for ongoing AI effectiveness.
Who Should Attend
The webinar is designed for technical and strategic decision-makers in medium to large organisations operating Microsoft 365 environments. This includes IT directors, data governance leads, information security managers, compliance officers and Microsoft 365 administrators. The content assumes familiarity with enterprise information management challenges and focuses on practical strategies rather than introductory concepts.
Industry Context
The rapid adoption of generative AI tools across enterprise environments has exposed longstanding gaps in data management practices. Organisations that previously tolerated sprawling, unstructured data repositories now face tangible consequences as AI amplifies the impact of poor data hygiene. This webinar reflects a growing recognition that AI readiness requires foundational work that many organisations deferred during earlier phases of cloud migration and digital transformation.