What We Think. What We've Published. What We've Learned.

The Future Of Artificial Intelligence: An Architecture-First Approach

Why the next wave of AI value depends on architecture, not model choice. The case for building AI into the data platform — not bolting it on — and the governance decisions that determine whether AI delivers at production scale or stalls in pilot purgatory.

Related: Onyx Impact Framework →

Transforming AI Pilots Into Profit Centers

Pilot purgatory is the single biggest waste of AI investment. The conditions required to move from successful pilot to production system — and why governance is the unlock, not the obstacle.

Related: 4-Week Fabric Accelerator →

Guardrails, Not Roadblocks: How C-Suite Leaders Can Foster AI Innovation

The leaders getting AI governance right aren't slowing innovation — they're accelerating it. Four principles for building guardrails that enable rather than constrain, and why the CDO's role is shifting from data custodian to AI steward.

Related: Onyx Impact Framework →

The Ramifications Of Losing The New Space Race

The geopolitical dimension of AI and data infrastructure — why the race to build sovereign AI capability matters for enterprises, not just governments, and what it means for technology strategy decisions being made today.

Best Practices For Leaders Integrating AI Into The Workplace

Most AI workplace rollouts fail at the change management layer, not the technology layer. Practical steps for leaders integrating AI tools — from identifying the right use cases to building governance structures that make adoption stick.

Related: Microsoft Copilot Adoption →

AI Will Enhance Your Job, Not Take It

The displacement narrative misunderstands what AI actually does to knowledge work. The case for AI as a productivity multiplier — and why the biggest risk is not job loss, it is the failure to reskill fast enough.

Adopting AI Legislation And Best Practices

Regulation is coming whether organisations are ready or not. Mapping the emerging AI legislative landscape — and why companies that govern AI proactively will be positioned as trusted operators, not scrambling to retrofit compliance.

Related: AI Governance Starter Kit →

Five Big Risks That Come With Your Finance Department Not Adopting AI

Finance teams that resist AI adoption aren't being cautious — they're accumulating risk. Five specific financial risks created by manual reporting, ungoverned data, and late AI adoption in the finance function.

Related: £93M in Documented Impact →

How To Enable Innovation And Efficiency With Data And AI

The organisations achieving the best ROI from data and AI are not the ones with the biggest budgets — they're the ones that connect technology investments to specific business outcomes. Enabling conditions for data-driven innovation at enterprise scale.

How To Build And Execute A Successful Data Strategy

Strategy documents that gather dust are worse than no strategy at all — they create false confidence. A practical framework for building a data strategy that connects to business outcomes with clear owners, milestones, and accountability.

Related: Onyx Strategy & Enablement →

How Data Can Supercharge Boardroom Decisions

Board-level decisions made without real-time data are increasingly a governance risk, not just a performance issue. The case for elevating data to the boardroom agenda — with practical examples of how executive teams use dashboards as decision instruments.

Related: See board-ready dashboards in practice →

How To Create A Data Platform For Sustainable Data-Driven Transformation

Most analytics platforms are built for current needs, not future scale. The case for the "digital core" model — a unified data platform that becomes the operating system of the business, not just the reporting layer.

Related: Microsoft Fabric Accelerator →

The Data Analytics Implementation Journey In Business And Finance

The implementation gap — the distance between a data strategy and a live production system — is where most programmes fail. Mapping the journey from strategy to production and identifying the three points where teams most commonly stall.

Six Reasons Why Executives Need Intelligence From Data

The gap between having data and having intelligence is where most enterprises are stuck. Six failure modes that leave executives flying blind — and what it takes to move from raw data to actionable insight at leadership speed.

The Executive's Guide To Data Analytics

A practical primer for non-technical executives who need to speak intelligently about data analytics with their teams, their boards, and their technology partners. Covers the vocabulary, the decisions, and the questions every executive should be asking.

Related: Book a Strategy Session →

Is Sentient AI Upon Us?

The earliest published piece — engaging with foundational questions about machine intelligence, the Turing Test, and what it means for a system to "think." Written before the GPT-4 wave.