The Importance of Information Governance in the Energy Industry

In an AI-enabled world, the payback on good Information Governance is faster than ever.

AI and Information Governance payback: faster than ever

Information Governance (IG) has long been held out as a way to improve the quality, completeness and trustworthiness of information and data. Many energy companies have embraced it; many still have not, and continue to experience problems with data quality, avoidable risk, and wasted time and budget.

What has changed in recent years is the stakes. A wave of new regulation, from the EU Artificial Intelligence Act and the Digital Operational Resilience Act (DORA) to the NIS2 Directive and the EU Data Act, has turned good information practice from a competitive nicety into a compliance obligation. At the same time, the rush to adopt artificial intelligence has made one thing very clear: AI is only as good as the governed data and metadata it is built on.

This article looks at the components of IG, how it is established and sustained, and why disciplined taxonomies and complete metadata are now the foundation of both regulatory compliance and AI readiness. Implementing good IG still requires sustained investment, but the payback – in business performance, defensible compliance and safe, scalable AI – has never been greater.

What has changed? Information Governance has always been important…

Many companies struggle to complete successful Information Management projects because the overall governance piece is either missing or incorrectly set up. The return on investment is usually low, the success of the project is limited, and that in turn puts future investment at risk. Establishing a governance framework before projects are initiated creates a longer-term, sustainable base for information management across the business.

The guiding logic has not changed: good information governance leads to good information outcomes, which in turn lead to good business outcomes. Information Governance is therefore inseparable from business strategy. It institutionalises sound ways of planning, acquiring, delivering, supporting and monitoring information, and it lets a company use its information to create value, reduce risk and gain competitive advantage.

What has changed is the operating environment.

Two forces now make Information Governance urgent rather than optional. The first is artificial intelligence: energy companies are deploying AI across exploration, production, asset integrity, safety and back-office functions, and every one of those use cases depends on trustworthy, well-described, well-governed data. The second is regulation: lawmakers in the EU, the UK and beyond have introduced rules on operational resilience, cybersecurity, data sharing and AI itself that place direct, auditable obligations on how organisations manage information.

Companies that already govern their information well are perfectly positioned to comply and to capitalise. Those that do not face mounting risk on both fronts.

A tightening regulatory environment

Recent legislation is moving information governance from good practice to legal obligation. The detail varies by jurisdiction, but the direction of travel is consistent worldwide: regulators expect organisations to know what data they hold, where it lives, who is accountable for it, how it is secured and shared, and how any AI built on it behaves. Energy companies, often operating digitally across borders, are squarely in scope. The most relevant instruments include:

The EU Artificial Intelligence Act. The world’s first comprehensive AI law entered into force in August 2024 and is being phased in. Bans on prohibited practices and AI-literacy duties have applied since February 2025; obligations for general-purpose AI models since August 2025; and the bulk of the high-risk regime, including data governance, record-keeping, transparency and human-oversight requirements, applies from August 2026.
^{https://eur-lex.europa.eu/eli/reg/2024/1689/oj}
The Digital Operational Resilience Act (DORA). In application since January 2025, DORA sets binding ICT risk-management, incident-reporting and third-party oversight rules for financial entities. It is directly relevant to energy companies with trading, treasury or financial-services arms, and to any firm acting as an ICT third-party provider to the financial sector. Even where it does not apply directly, DORA has become the reference model for what regulators expect of operational resilience — including a maintained register of information on ICT arrangements, which is fundamentally a governance and metadata exercise.
^{https://eur-lex.europa.eu/eli/reg/2022/2554/oj/eng}
The NIS2 Directive. NIS2 expands EU cybersecurity obligations across critical sectors and names energy explicitly, SOCI does the same in Australia, as will the UK’s Cyber Security and Resilience Act, when it receives Royal Assent later in 2026. Essential and important entities must implement proportionate technical and organisational measures, report incidents, and hold management bodies personally accountable for compliance, with fines up to €10 million or 2% of global turnover.
^{https://eur-lex.europa.eu/eli/dir/2022/2555/oj; https://www.legislation.gov.au/C2018A00029/latest}
The EU Data Act. In application since September 2025, it gives the user of a connected product the right to access the data it generates and share it with a third party of their choice. From September 2026 new equipment must be accessible by design. Upstream is densely sensorised (drilling tools, ESPs, subsea instrumentation, turbines, rotating-equipment monitoring), so much of this kit is in scope. For an E&P operator it is both a lever against OEM data lock-in and an obligation — and exercising or resisting these rights, including the trade-secret and safety carve-outs for sensitive subsurface data, depends on being able to identify, describe and classify the data each asset generates. That is governed metadata in action.
^{https://eur-lex.europa.eu/eli/reg/2023/2854/oj/eng}
Data protection and sector rules. The GDPR and UK GDPR continue to require lawful, accountable handling of personal data, and many jurisdictions outside Europe, are introducing comparable privacy, cybersecurity and AI rules (for example, the LGPD in Brazil, Vietnam’s AI law, and forthcoming presidential regulations in Indonesia on AI). For multinational operators, the practical answer is not to track every statute separately but to govern information well enough to satisfy all of them
^{https://eur-lex.europa.eu/eli/reg/2016/679/oj; https://www.legislation.gov.uk/ukpga/2018/12}

The common thread is unmistakable, and also a growing, consistent theme in legislation across the major oil and gas nations of the world. Governments assumes the organisation can answer basic questions about its information — what it is, where it is, who owns it, how good it is, and on what basis it can be used. That is precisely what an Information Governance framework delivers.

The building blocks of information governance

Sponsorship

Support should focus on two groups. The first is an IG group that acts as the decision-making body for Information Management (IM) projects, services and initiatives, comprising senior executives, representatives from across business functions and a senior IM lead. It assigns ownership, oversees data and information quality, manages related risk and drives the cultural change that makes IM stick. The second is the user community itself: their support, or lack of it, determines the success or failure of any initiative.

Principles & standards

A consistent approach to IM, covering how information is managed, accessed and secured, relevant service levels, and practical guidance on implementation. Standards now also need to address data classification, lawful use and entitlement, and the acceptable use of AI on company information.

People & organisation

Clear roles defining who owns, is responsible for, and is accountable for data and information, including the IG group (oversight and control), data coordinators (proactive day-to-day management) and data owners (senior users who control and publish information). The organisation needs an information-centric view: information is the lifeblood of the business.

Controls

Mechanisms that align behaviour to the standards, demonstrate that IM risks are managed, and show culture is shifting. Data-quality scorecards and dashboards that track quality over time, and the policing of standards and ownership through performance objectives, rewards and consequences. Controls increasingly double as evidence for regulators.

Technology

The tooling that holds governance in place. Including data-quality scorecards, data dictionaries and taxonomies that give the company consistent definitions, and a stable, consistent platform. This is also the layer that exposes governed data to search, retrieval and AI.

Processes

The key processes (data-quality management, change management, compliance assurance and others) that the business agrees, follows and improves over time.

Data ethics and AI governance is emerging as a seventh, cross-cutting component, setting clear principles on how information and AI may be used, who signs off, and how decisions are recorded and audited. This keeps the framework aligned with the EU AI Act and equivalent expectations elsewhere.

Information
Governance

Why taxonomies and complete metadata are the foundation

Taxonomies and complete, consistent metadata are the foundation on which every other benefit rests. This is the core message of this article. They are not back-office housekeeping: they are the mechanism that makes information findable, trustworthy, shareable, compliant and usable by AI.

A taxonomy provides the shared vocabulary – the agreed structure of business processes, disciplines, asset types, record types, jurisdictions and the rest – that lets an entire organisation describe its information the same way. Complete metadata applies that vocabulary to each piece of content, so the company knows what something is, where it came from, how good it is, who owns it and on what basis it can be used. Together they deliver compounding returns:

Findability. People, and machines, locate the right information quickly, and correctly.
Quality and trust. Metadata makes quality measurable, so scorecards mean something and decisions rest on data that can be trusted.
Avoided cost. Knowing what already exists prevents buying the same data twice and repeating work that has already been done.
Compliance by design. Classification, ownership, retention and entitlement metadata are exactly what NIS2, DORA, the Data Act and data-protection law require an organisation to be able to demonstrate.
AI that works. A well-implemented taxonomy and metadata are what let RAG, knowledge graphs and AI assistants return accurate, sourced answers rather than plausible guesses.

The investment is significant, but it pays back many times over. A single, well-maintained taxonomy and a discipline of complete metadata deliver across search, compliance, cost control and AI simultaneously. Getting the foundations right matters more than any individual tool or project.

Setting up information governance

So, given the clear value of a taxonomy, what is the most effective way to acquire one? Our view hasn’t changed over the last 26 years, but the number and weighting of contributing factors have shifted.

Engage senior stakeholders and secure support and sponsorship. Without these, the initiative goes no further.
Establish the Information Governance group and formalise the other roles — information owners and supporting roles — across the business.
Create standards and communicate them, so the business gains ownership and accepts the new ways of working. Develop them with a cross-functional group plus outside expertise to get the right mix of input and experience.
Build the toolset. Scope varies with ambition, but essentials include data-quality scorecards and dashboards, a consistent data dictionary and taxonomy, and a data model that links the business together. Specialist providers can build these from industry best practice, with low-cost outsourced maintenance and support.
Establish processes and controls. The key process is IG compliance, determining how it is assured and what the consequences of non-compliance are. This is increasingly where regulatory evidence is generated.
Communicate with the business. This takes two forms: continual, targeted communication to key stakeholders who will promote the effort, and sustained change management and support for end users.
Provide training and support. Unless significant change-management expertise exists in-house, use an external agent. The cultural change behind IG cannot be rushed; the business needs time to understand and accept new behaviours, so build continuous, low-level education into support plans and budgets.
Assess and improve continually. The work does not stop, ever. Standards, tools and processes will need to change as circumstances do, for example, adjusting data-quality dashboards as different data types or attributes become more important, or as new regulation and AI use cases emerge

Making it sustainable

Information Governance is challenging mainly because it has no start and finish date. It is a continuous effort that must be driven into the business for the long term. Its sustainability depends on a few factors:

Sponsorship and executive understanding. Information Governance needs sustained executive sponsorship, understanding and active promotion. Executives must grasp the drivers, benefits and risks, and increasingly the regulatory accountability that now rests personally with senior management. They should see near-term results that encourage promotion of, and identification with the initiative.
Results. Pinpoint and achieve quick wins early so stakeholders see the benefits. Set specific targets, such as better data-quality management, basic ownership of master-data entities, or an AI use case unblocked by clean data, then run a benefits-realisation exercise that ties framework deployment back to business objectives.
Complexity. Tailor the framework to the size and type of company. A framework designed for a super-major will fail in a small explorer. Ownership, processes and standards should all reflect what is realistically achievable.
Business culture. Where the organisation genuinely wants to manage information better, the odds of success rise. A change programme that gradually shifts mindsets helps; the message to the user community is that “this is needed, and this will help, for the long term.”

Summary

Information Governance is not for the faint-hearted: it takes significant time, effort and the ability to influence key stakeholders. But energy companies derive enormous value from it. Information Governance reduces risk, lowers cost and improves performance and productivity, and the case is now stronger than ever. Regulation has made disciplined information management a legal obligation, and AI has made it the precondition for one of the biggest opportunities of the century.

Because Information Governance compliance is essential, those who meet its requirements should be recognised and those who do not should be helped to change. Publicising good behaviour matters; cultural change makes good IM easier to deploy and sustain. The steps are common to all implementations, but pace and complexity must be tailored to the organisation. It is better to begin with a few key elements (Governance-“lite”) and build on success than to start with an onerous framework few people understand and even fewer can implement.

Above all, get the foundations right. Disciplined taxonomies and complete metadata are what make information findable, trustworthy, compliant and AI-ready, and they pay back across every one of those dimensions at once. Specialist energy information-management companies (such as Flare Solutions) can accelerate the journey, bringing experience from other operators and industries to design and deploy a practical framework in a reasonable timeframe. But the push and sponsorship must come from senior executives willing to promote and support the initiative from the outset, and keep supporting it for the long term.

Why Flare?

Formed in 1998 by a team with a background in geoscience and petroleum engineering, Flare brings extensive industry experience gained at management, operations and technical levels within energy companies and the energy service sector. The Flare team has developed a unique, holistic approach to managing knowledge, information and data that focuses on real business needs, not technology for its own sake.

Since its formation, Flare has worked with energy companies around the world, earning a reputation for excellence and innovation across engagements ranging from information management strategy to workflow and process improvement projects, for organisations from small independents to large multinationals, as well as governments, service organisations and industry groups.