Your AI Strategy is Missing One Critical Element

Originally appeared in Fast Company. Read the original article here.

AI hype has convinced executives that it is the solution to every business challenge. However, a recent MIT study found that only 5% of AI pilots create value, while the other 95% yield zero return.

Data governance offers a discipline that determines whether your AI systems produce reliable decisions or costly mistakes. Successful AI implementations and informed business decisions rely on well-governed data that provides accurate, secure, and accessible information. For most companies, well-governed data is their biggest untapped advantage.

Here’s the catch: Treat data governance like an IT concern, and you’ll struggle to get past the experimental phase.

The Perception Problem

The root causes of AI failure become clear when examining the data governance landscape. An Actian study found that 83% of organizations face governance and compliance challenges. Yet C-suite leaders rate their data governance maturity 12% higher than operational managers and analysts who work with data daily.

This overlooked discipline separates market leaders from followers.

To understand the consequences of weak data governance, look at any given week’s news headlines to see the impact on businesses worldwide.

In the past, poor data quality resulted in inconvenient dashboards and occasionally revised reports. Today, that same questionable data represents potential security breaches, reputational damage, and massive regulatory fines.

For example, since GDPR enforcement began in 2018, European regulators have issued over €5.65 billion in fines. The largest category of fines? Non-compliance with basic data processing principles.

How Data Governance Enables AI Success

Winning companies organize and govern data that matters. They embed governance by design to catch quality issues at the start, rather than retroactively cleaning up issues later.

As a result, employees can easily find the data necessary when needed, and can trust that data enough to act decisively. When employees trust the data, they spend more time creating value and less time second-guessing information.

More importantly, AI systems act on the same trusted data to make reliable automated decisions at scale. The benefits compound quickly, offering strategic agility.

Why Data Governance Requires Executive Leadership

Strong data foundations require deliberate leadership from the top. Data governance fails when executives delegate it entirely to IT or treat it as a compliance checkbox. Governance succeeds when executives champion it as an enabler of AI investments to deliver value.

In addition to AI, data governance touches every strategic priority in your business. Board reports, risk management, competitive positioning, and regulatory compliance all depend on clean data.

The reality is that cultural change starts at the top. If leadership treats data governance as optional, everyone else will likely follow suit. If executives prioritize data quality and security in decision-making, data governance becomes part of the company’s DNA.

Beyond cultural change, effective governance requires investment in tools, policies, processes, training, and resources. With the support of top leadership, it receives the funding it deserves.

Not long ago, companies treated cybersecurity as an IT concern. According to the Harvard Law School Forum on Corporate Governance, organizations that elevated cybersecurity through board oversight and specialized risk or audit committees realized a 372% higher shareholder return than peers without this structure.

Data governance is following the same pattern, but the urgency of AI raises the stakes and compresses the timeline for action.

The AI Amplification Effect

Data governance challenges become more dangerous when AI enters the picture. AI uses data to automatically make decisions that can multiply every governance failure exponentially.

Poor data quality, perhaps, was  just merely annoying in the past, but is a serious risk when AI acts on it. If your data isn’t properly governed and AI is used inappropriately, you’re not just dealing with a bad report. You could be facing simultaneous events of algorithmic bias, compliance violations, or thousands of poor customer decisions.

Consider these scenarios:

• An AI pricing algorithm using customer data begins charging different rates, inadvertently discriminating against protected groups and creating legal exposure.
• An AI-powered customer service agent trained on purchase history starts inferring health conditions from buying patterns, causing systematic HIPAA penalties.
• A recommendation engine trained on outdated inventory data suggests unavailable products to thousands of customers, damaging satisfaction scores.

However, the inverse is also true — well-governed data becomes a strategic multiplier. Organizations with strong governance frameworks can deploy AI for:

• Automated pricing that’s both competitive and compliant.
• Customer service systems that respect privacy while personalizing experiences.
• Recommendation engines that consistently suggest relevant, available products.

When companies eliminate data uncertainty, they can launch AI initiatives in weeks rather than months, automate decisions that others handle manually, and beat their competitors to market.

The Strategic Imperative

With strong governance, companies deploy AI with confidence. Those without data governance fall behind. The gap widens every quarter because data governance has become today’s strategic imperative and tomorrow’s innovation engine.

However, successful governance relies on executive sponsorship and instilling the discipline that determines whether AI delivers lasting business value or costly disappointment.

The real decision, then, is not whether to invest in data governance. It’s whether you are willing to let other competitors seize that advantage first. Companies with leaders who commit now will set the pace for the next wave of AI-driven transformation. Everyone else will follow.

About Marc Potter

Marc Potter serves as Chief Executive Officer for Actian, originally joining the company as Chief Revenue and Operations Officer in 2019. Since being named CEO in January 2023, Marc has been responsible for driving Actian’s long-term strategic vision and innovations to position Actian to be the essential provider of data intelligence solutions that enable confident, data-driven organizations. With over 20 years of leadership experience in information technology and enterprise software systems, Marc believes in creating an employee-first culture that prioritizes employee engagement, open communication, and professional development.