Defining and Reporting Data Risk in Banking
As regulatory expectations increase, how do banks define, measure and communicate data risk in a way that drives ownership and action?
Defining the Scope for Governing Data Within Data Products
As organisations scale data products, how do they apply governance proportionately without creating unnecessary overhead?
Embedding Data Governance into Projects and Business Operations
Explore how peers translate governance policy into practical responsibilities, controls and measures within delivery and everyday operations.
Building Decision Literacy: Helping Teams Challenge and Act on AI Recommendations
Explore how peers help employees interpret AI recommendations, exercise judgement and remain accountable for their decisions.
Controlling AI Cost at Scale: Compute, Usage and Unit Economics
Examine how organisations connect the full cost of AI to business outcomes and intervene when the economics no longer hold.
Who Funds Shared Data Foundations? Ownership, Co-Investment and Value Attribution
Explore how peers decide which shared data capabilities merit central investment and how funding and value are allocated across the business.
Managing Multiple AI Models and Providers: Standards, Switching Costs and Vendor Risk
Explore how peers set model and provider standards while preserving choice, controlling dependency and preparing for future change.
Rerun: Breaking Down Data Silos In Complex Organisations
Discuss how organisations are connecting fragmented data teams and capabilities while preserving business ownership and agility. Share practical approaches to creating consistent standards without slowing down innovation.
Rerun: Reimagining Data Stewardship in an AI-First World
Explore how AI is transforming data stewardship by automating repetitive tasks and allowing stewards to focus on governance, ownership and decision-making. Discuss how organisations can redesign stewardship roles to increase engagement and accountability.
Modernising Regulatory Data Production for the AI Era
Discover how cloud, data products and AI are reshaping regulatory data production and what the next era of trusted, intelligent reporting could look like.
Aligning Decentralised Data and AI Capabilities with Enterprise Strategy
Explore how leading organisations are balancing decentralised AI innovation with enterprise governance, architecture and investment.
AI governance in banking: Scaling oversight without slowing innovation
A banking discussion between DataIQ clients examined the pressures surrounding governance while trying to scale AI adoption.
Designing Enterprise Trust for Data and AI: The Back-of-the-House Data Reliability Operating Model
Modern data platforms may be faster and more scalable, but that does not mean their outputs are trusted. As AI raises the stakes, data leaders need to ask a harder question: is reliability something they are monitoring, or something they have deliberately engineered?
Breaking Down Data Silos In Complex Organisations
Discuss how organisations are connecting fragmented data teams and capabilities while preserving business ownership and agility. Share practical approaches to creating consistent standards without slowing down innovation.
Reimagining Data Stewardship in an AI-First World
Explore how AI is transforming data stewardship by automating repetitive tasks and allowing stewards to focus on governance, ownership and decision-making. Discuss how organisations can redesign stewardship roles to increase engagement and accountability.
EU AI Act Delays Create Breathing Room for AI Governance
The latest updates to the timeline for the EU AI Act provide some extra space for data and AI leaders, but vigilance needs to remain high for all things governance.
Evolving Data Governance for the AI Era in Regulated Industries
Explore how regulated organisations are evolving governance to support AI, balance compliance with agility, and align data, model risk and AI oversight.
Navigating AI Risk: Building Resilient and Responsible Data Practices
Data and AI leaders need to develop sturdy data practices that can ensure governance in an era of scaling while monitoring and deflecting risk.
Governance is the Route from AI Pilots to Enterprise Performance
As organisations find embracing AI experimentation easier than ever before, AI production remains an operating commitment. Governance has therefore arrived front and centre, acting as the mechanism that allows AI to scale with trust.
Governing Critical Data Elements: Best Practice for Mature Regulated Organisations in the US
How are leading US financial institutions identifying and governing critical data elements while balancing risk, ownership, and operational efficiency?