Tagged with: #data-strategy

The strategic value of data is no longer in question. The next frontier is data whose meaning and relationships are explicit enough for machines to reason over rather than merely retrieve. Unstructured information must be interpreted by whoever consumes it, whether that is a person reading a report or an AI system generating an answer. Structured information makes explicit the relationships required for traceability, verification, and defensible reasoning at scale. In this article, I argue that ontologies and the knowledge graphs built upon them have moved from technical infrastructure into Board territory, because they increasingly determine what an organisation officially knows, what its AI systems can work with, and where durable advantage is created.

Boards apply rigorous stewardship to physical assets: regular condition assessments, clear ownership, maintenance investment, impairment testing. Data assets — which increasingly drive competitive advantage — receive none of these disciplines. The gap isn’t technical; it’s governance. Accounting standards render data invisible on the balance sheet, so Boards govern it as though it doesn’t exist. This article argues for balance-sheet thinking applied to data, using the AI Centre of Excellence as the governance vehicle. For Boards, the question isn’t whether data belongs on the balance sheet; it’s whether you’ll steward it as if it does.

Last night, I had the pleasure of returning to the Chief Wine Officer event series on behalf of AWS, this time addressing leaders from private equity portfolio companies on a topic close to my heart: turning organisational data into strategic value. The evening, hosted at Spring at Somerset House, brought together executives eager to explore how to accelerate value creation through data monetisation within PE timeframes.

In 1998, I walked into the headquarters of our newly acquired newspaper group in Leeds, a result of a private equity-backed management buyout of United News & Media’s regional newspaper and magazine titles. Tasked with ‘doing the internet’, I found a small semblance of online activity in the form of a basic advertising website for the Yorkshire Post. A couple of weeks of getting my feet under my desk yielded a digital goldmine - 271 years of content waiting to be transformed into digital assets.

Last week, I had the privilege of delivering a keynote presentation at Monday.com’s Elevate conference in London. The topic, “Leveraging data and artificial intelligence (AI) for organisational transformation,” allowed me to challenge some common misconceptions about AI adoption and share practical insights on harnessing the power of existing data. In this post, I outline the key themes discussed and provide some additional context.

Earlier this week, I got the opportunity to speak at our Amazon Web Services (AWS) office in London, to an audience of Private Equity firms and their portfolio company executives about driving value creation through AI and data. The presentation focused on how Private Equity firms and their portfolio companies can drive value creation through AI and data. I also took the opportunity to introduce a new concept called the AI Stages of Adoption (AISA), which is designed to help organisations assess their maturity and readiness for AI adoption.