Insights

Traditional consulting scales by adding bodies. The AI era demands something different — observable outcomes, operational governance, and evidence by design. Seven questions to ask any consulting partner to find out whether their delivery model has genuinely changed, or just their pitch.

Traditional consulting is structurally incompatible with the AI era. That's not commentary — it's a design problem. The pyramid was built to solve a production constraint that no longer exists. Here's why the economics have broken, and why the firms most threatened are the ones currently selling AI transformation.

The economics of consulting have shifted. AI has commoditised the output layer — frameworks, slide decks, operating model templates. What clients now pay a premium for is what AI cannot reliably provide in regulated industries: accountable delivery, operational integration, and evidence.

A BearingNode series on the AI era transformation of management consulting. Six questions. One uncomfortable answer. Written for CDOs, CIOs, and senior leaders in regulated industries who are tired of transformation programmes that end with a governance framework no one owns.

Better decisions don't come from more dashboards, faster AI, or bigger datasets alone. Barry Green, Advisory Board Member at BearingNode and co-author of Data Means Business, argues that good decisions require whole-body thinking — integrating logic, experience, intuition, ethical judgement, and organisational context.

Two words. Four meanings. None of them accidental. In the AI era, the premium has moved to trustworthy execution. BearingNode's name encodes exactly what modern data, analytics, and AI consulting must be.

Explore the unique economic characteristics of data and information assets, including their non-rivalrous nature, network effects, and strategic value creation in the digital economy.

A common mistake in data conversations is to treat governance and observability as interchangeable. They are not. D/I O11y overlaps with governance, compliance, management and strategy — but it is distinct from all four.

Daniel Rolles participated in FIMA 2025 at The Kia Oval in London, sharing insights on the convergence of Data Governance and AI Governance with industry leaders from across Europe's financial services sector.

Gen AI projects reveal inadequacy of inherited frameworks. Learn why 95% of GenAI pilots fail not from technical risks, but from unvalidated assumptions about adoption, workflow fit, and business value—and how to navigate uncertainty rather than just manage risk.

The EDM Council's DataVision EMEA 2025 revealed three fundamental shifts reshaping data governance in the AI era: the move from governance by policy to governance by evidence, the evolution of standards frameworks, and the challenges of federated data management at scale.

The Rise of Data and Information Observability: Moving Beyond Traditional Methods.

BearingNode is proud to introduce our Data and Information Observability (D/I O11y) framework.

Explore the critical distinctions between data and information with practical frameworks for data leaders. Learn how context transforms raw data into actionable information for strategic decision-making.