As legal departments take on greater responsibility for AI, privacy, cybersecurity and litigation readiness, understanding enterprise data has never been more critical.
by Greg Mazares, Sr., CEO of Purpose Legal and Hire Counsel
This summer, a very popular destination is on the minds of CEOs, CFOs, COOs, CIOs, CDOs, and General Counsel. It’s the enterprise data lake.
Organizations everywhere are investing millions to consolidate decades of fragmented enterprise information into centralized repositories with one overriding goal: unlocking the full potential of artificial intelligence. This architecture eliminates data silos, allowing organizations to train machine learning models on diverse datasets and feed real-time information into AI agents.
The urgency is understandable. AI has moved from experimentation to enterprise adoption. Yet according to McKinsey, nearly two-thirds of organizations have not yet begun scaling AI across their businesses despite its widespread use. The missing ingredient isn’t more AI. It’s better-prepared enterprise information.
While this is a smart investment, it’s also creating a dangerous misconception.
The strategic value of enterprise data lies not in where it’s stored, but in how well it’s understood and used. Building a data lake doesn’t make an organization AI-ready any more than arriving at Lake Como guarantees a great vacation.
That may sound like an odd metaphor, but it’s surprisingly accurate. Over the past year, I’ve spoken with business leaders across the legal technology and services industry who are investing heavily in enterprise data initiatives. In fact, I personally know of at least a half-dozen organizations that are currently undertaking major data lake projects, each driven by the same objective: bring together years of fragmented, siloed information so the business can finally unlock the potential of artificial intelligence.
AI Didn’t Create the Problem. It Exposed It.
Why the rush to build data lakes now?
Because AI has changed the economics of storing, accessing, and using enterprise information.
For the first time, organizations can derive meaningful business value from enormous volumes of unstructured enterprise information, but only if that information is organized, governed, and understood.
Artificial intelligence has made the need for data readiness indispensable.
At first blush it may feel like enterprise AI has created data chaos; however, it’s really the opposite. It’s simply exposed years of technical debt, fragmented information, and inconsistent governance that organizations could previously afford to ignore.
Data lives everywhere. The challenge isn’t collecting information anymore, but knowing what matters.
Microsoft 365. Teams. Slack. SharePoint. Legacy file shares. Cloud repositories. Email archives. Departmental applications. Personal drives. The average company generates and stores staggering amounts of information across dozens, and often hundreds, of systems.
Bringing that information together is an important milestone. But aggregation alone still doesn’t answer the questions that matter most: Do you know where your sensitive information resides? Can you identify duplicate or obsolete data? Which employees own which information? What should be preserved? What can be defensibly deleted?
If litigation, a regulatory inquiry, or an internal investigation began tomorrow, could you quickly locate the information that matters? A company that spends three weeks identifying custodians and locating responsive data isn’t suffering from an AI problem. It’s suffering from a data readiness problem.
What many leaders misunderstand is these aren’t technology questions. They’re business questions with legal, financial, regulatory, and operational consequences.
Data Infrastructure Isn’t the Same as Data Readiness
Think about planning your summer vacation. Planning a vacation requires much more than choosing a destination. You need reservations, an itinerary, activities, and contingency plans.
Data lakes are remarkably similar. They’re foundational infrastructure; they create the opportunity to organize information at scale, but they don’t automatically provide visibility, governance, context, or confidence.
Too often, organizations celebrate completion of a data lake initiative only to discover they’re still struggling with the same operational challenges they faced before:
- The Legal Department can’t quickly identify key custodians.
- Compliance can’t locate regulated information.
- Privacy teams struggle to fulfill data subject access requests.
- Security teams don’t know where sensitive information has proliferated.
- Investigators still spend weeks locating relevant evidence before they can begin answering substantive questions.
While the data might now be centralized, the organization still isn’t “data ready.”
Legal Departments and Law Firms Have Quietly Become Data Organizations
What we’ve seen recently is a dramatic shift inside corporate legal departments and law firms, where these institutions have evolved into data organizations.
Twenty years ago, General Counsel primarily managed legal risk. Today they increasingly manage data risk.
Not long ago, corporate legal teams primarily focused on contracts, outside counsel management, litigation, and investigations. Today, their responsibilities are far broader and more intertwined.
That shift is profound.
Legal departments increasingly sit at the intersection of AI governance, privacy, cybersecurity, internal investigations, regulatory compliance, information governance, and litigation readiness. It’s a dramatic expansion of the legal department’s strategic role. And each of these disciplines depends on one foundational capability: understanding enterprise data, starting with where it is located.
Whether they planned for it or not, general counsel are becoming enterprise data leaders, expected to answer and advise on questions that extend well beyond traditional legal advice. It’s common now for them to get asked: Where is our regulated data? Is it “ready” for litigation or investigations? Can we preserve it? Can we investigate it? Can we produce it? Can we defend our decisions?
Those answers require far more than sophisticated technology. They require continuous understanding of the information flowing through their respective organizations.
The Next Competitive Advantage: Perpetual Data Readiness
Competitive advantage no longer belongs to the organizations with the most data. It belongs to organizations that understand their existing data the best.
They understand where information lives, how it’s connected, what information creates value, where sensitive data resides, and where risk is accumulating. Most importantly, they can act on that knowledge before a business event forces them to.
That capability has implications far beyond litigation. It improves regulatory response, privacy compliance, cyber investigations, mergers and acquisitions, insider threat detection, records management, and even AI performance itself.
After all, AI is only as effective as the quality of the information it can reliably access.
The organizations pulling ahead aren’t waiting until litigation, cyber incidents, or regulatory inquiries occur before they begin understanding their enterprise information. They maintain continuous understanding of their enterprise information so they can respond confidently whenever those events occur. They’re building perpetual data readiness.
That means continuously knowing what information exists, where it resides, who owns it, how sensitive it is, and how quickly it can be acted upon.
In an AI-enabled enterprise, data readiness isn’t a project. It’s an operating discipline.
A Data Lake Stores Information. Data Readiness Creates Business Advantage.
The excitement surrounding enterprise AI isn’t going away. Nor should it. Organizations that invest thoughtfully in modern data infrastructure are laying an important foundation for the future.
But infrastructure should never be confused with strategy.
The organizations that succeed in the AI era won’t necessarily be those with the largest data lakes.
They’ll be the ones that understand their enterprise information deeply and can act on it before legal, regulatory, or business events demand it.
The Final Destination Isn’t the Data Lake
In the age of AI, the ultimate destination is achieving the level of data readiness that turns information into action, uncertainty into confidence, and reaction into preparedness.
Understanding your data—not merely storing it—will be one of the defining competitive advantages of the next decade. The organizations that simply collect data will continue searching for answers long after they’ve arrived at the lake.
So yes, this summer it seems like everyone is vacationing at the data lake.
The real challenge was never about who reaches the lake first. It’s who knows how to navigate it.
To get a better idea of your litigation readiness, contact us for a Perpetual Data Readiness Assessment.
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About the Author
Greg Mazares, Sr., CEO of PurposeLegal, is a veteran senior executive in the legal services and legal technology industry with more than three decades of experience helping law firms and corporate legal departments navigate complex litigation, investigations, regulatory matters, and enterprise data challenges. Throughout his career, he has built, and led innovative companies focused on eDiscovery, managed review, flexible legal staffing, data forensics, information governance, and AI-enabled legal solutions. A frequent writer and speaker on the intersection of artificial intelligence, enterprise data, and the evolving legal profession, he advocates for helping organizations achieve perpetual data readiness to improve decision-making, reduce risk, and unlock the full value of artificial intelligence.
Reprinted with permission from the August 5th, 2026 edition of the “Corporate Counsel” © 2026 ALM Global Properties, LLC. All rights reserved. Further duplication without permission is prohibited, contact 877-256-2472 or asset-and-logo-licensing@alm.com.
