AI-Native Business Will Change the Evidence Landscape

Lessons from the 2026 ACC Legal Operations and CLOC Conferences

Over the past few weeks, I had the opportunity to attend both the 2026 ACC Legal Operations Conference and the Corporate Legal Operations Consortium (CLOC) Global Institute, both held in Chicago. I have been attending these very conferences for the better part of a decade, and the level of energy, urgency, and genuine excitement from the legal operations community has never been higher.

While each event had its own tone and audience, the overarching themes were remarkably consistent. Corporate legal departments are no longer asking whether artificial intelligence will impact the practice and business of law. That question has largely been answered. The more pressing questions now are how quickly AI should be adopted, where it should be applied, how it should be governed, and how legal departments can ensure that the use of AI creates measurable value without compromising judgment, transparency, or trust.

What stood out most was not simply the enthusiasm around AI. It was the tension beneath that enthusiasm. Legal teams know they need to move faster, and the pressure is not only coming from within the legal department. General counsel, CEOs, boards, and other business leaders are increasingly asking how AI will be used to improve efficiency, reduce cost, accelerate decision-making, and change how legal work is delivered. But in many cases, that pressure is arriving before the direction is fully defined. The desire is clear. The operating model is still being built.

That is where legal operations has always been most valuable. Legal operations sits at the intersection of people, process, technology, data, outside counsel, vendors, and business expectations. It is the function most capable of translating broad AI ambition into practical execution. But as the conversations at ACC Legal Operations and CLOC made clear, the AI discussion is quickly expanding beyond internal legal department efficiency. The larger shift is that businesses themselves are becoming AI-native, and that will have significant implications for litigation, investigations, discovery, and the future evidence landscape.

How Much Are We Willing to Automate?

One of the most thought-provoking questions raised during the conference discussions came from the keynote speaker Zach Kass, the former go to market leader at OpenAI, who asked, in substance, how much we are actually willing to automate. Where do we stop?

That question may become one of the defining issues for legal departments over the next several years. The question is no longer simply whether AI can perform more legal work. Increasingly, it can. The more important question is where legal departments want automation to stop and where human judgment must remain central.

For legal teams, the answer cannot be binary. The goal should not be to automate everything possible, nor should it be to resist automation simply because the work has historically been performed by people. The better approach is to determine which tasks are repeatable, data-driven, measurable, and appropriate for automation, and which decisions still require legal judgment, business context, professional skepticism, or human accountability.

Corporate legal departments do not just need an AI strategy. They need an automation philosophy.

A practical framework may be this: automate the repeatable, accelerate the analytical, and preserve the judgmental. Repetitive tasks, structured workflows, data classification, reporting, and first-pass analysis may be strong candidates for automation. More complex analytical work may be accelerated by AI, but still requires human validation and context. The most judgment-driven decisions, including legal advice, risk tolerance, litigation strategy, privilege calls in close cases, regulatory sensitivity, and client counseling, still require people who understand the business, the law, and the consequences of getting it wrong.

This is not a limitation of AI. It is a recognition that the value of AI in legal work depends on thoughtful placement. The question is not whether AI belongs in the legal department. It does. The question is where it belongs, how it is supervised, and how its role is explained.

Transparency and Trust Will Define the Next Phase

Another consistent theme was the growing expectation that law firms and legal service providers be transparent about their use of AI. Corporate legal departments are not simply asking whether their partners are using AI. They increasingly want to understand how it is being used, where it is being used, what controls are in place, and whether the benefits are being shared with the client.

This will likely become a major evolution in outside counsel and vendor management. If a law firm is using AI to reduce drafting time, summarize records, support research, analyze documents, or streamline review, clients will want to know how that changes the staffing model, the budget, the timeline, and the quality-control process. The same applies to service providers. It is no longer enough to say that a platform or process is “AI-enabled.” Legal departments need to understand what that means in practice, how outputs are validated, what human oversight exists, and what measurable impact is being delivered.

AI may create efficiency, but transparency will determine whether clients trust the efficiency.

This is also why relationships may become more important, not less. As legal work becomes more technology-enabled, the need for trust becomes greater. Internal legal teams need alignment with business stakeholders. Legal operations teams need credibility with lawyers who may be skeptical of new tools. Corporate clients need confidence that their law firms and providers are using AI responsibly. Outside partners need to understand not only the technology, but the client’s risk tolerance, business objectives, data environment, and preferred operating model.

AI may automate tasks, but it does not replace trust. It does not replace institutional knowledge. It does not replace accountability. And it does not replace the need for partners who can help legal departments make practical decisions about when to use technology, when to pause, and when to rely on human judgment.

AI-Native Business Will Change the Evidence Landscape

The conference conversation understandably focused on how legal departments will use AI. But the larger shift may come from how the business uses AI.

Across the enterprise, AI is beginning to move into ordinary business functions. Sales teams are using AI to summarize customer interactions and prepare follow-up communications. HR teams are using AI-enabled platforms to manage employee information and evaluate trends. Finance teams are using automation to analyze transactions, forecast risk, and generate reports. Product, marketing, compliance, and customer service teams are all beginning to rely on systems that do more than store information. They help create it, shape it, summarize it, route it, and recommend action.

That changes the evidence landscape.

For years, litigation and investigations have been expanding beyond email and traditional documents into chat, collaboration platforms, mobile data, images, audio, structured systems, and ephemeral communications. AI-native business workflows represent the next major layer. Future disputes may require legal teams to understand not only what a person wrote or approved, but what system helped generate the content, what prompt or input shaped the output, what data source informed the response, whether the output was edited, and how the final decision was made.

This will create new questions for litigation teams, law firms, and service providers. What is the record? Where does it live? Is it structured, semi-structured, or unstructured? Was it created by a person, suggested by a system, or produced through a combination of both? What metadata matters? What context is needed to understand the decision? What needs to be preserved? What can be defensibly excluded? How should it be reviewed?

The impact will not be limited to data volume, although volume will certainly be part of it. The more significant challenge will be data complexity. Legal teams will be asked to make sense of information that does not fit neatly into traditional document review models. Structured data, system logs, prompts, outputs, approvals, embedded summaries, workflow histories, and AI-assisted decisions may all become part of the factual record.

This is where the litigation industry will need to evolve. Corporations will need to think more deliberately about how AI-enabled business records are governed, retained, and preserved. Law firms will need to advise clients on how these new evidence sources affect strategy, risk, discovery, and defensibility. Providers will need to help clients normalize, analyze, and review increasingly complex data types in ways that are practical, repeatable, and explainable.

The question is not only how legal departments will use AI to do their work. It is how legal departments will respond when the business itself is using AI to do its work.

The Industry Will Move Further Left

As the evidence landscape changes, litigation and investigations will need to move further left, closer to where data resides and business decisions are made. Waiting until data is collected, processed, and loaded into a review platform will no longer be enough. Legal teams will need to understand the systems, workflows, and data sources earlier in the matter lifecycle.

This shift is already underway. In many matters, the most important decisions are made before traditional document review begins. What systems should be targeted? Which custodians or data sources actually matter? How should structured data be handled? What can be defensibly excluded? Which documents, messages, images, or records should be prioritized? Where might privilege risk exist? Where can analytics help reduce noise before it becomes cost?

AI-native business workflows will only accelerate the importance of those early decisions. If information is created across complex platforms, structured systems, collaborative tools, and AI-enabled applications, legal teams will need a more sophisticated understanding of the data before review begins in earnest.

This is where the role of technology and service providers will continue to expand. The next generation of litigation support will not be defined solely by processing data, hosting documents, or staffing review teams. It will be defined by the ability to help clients understand complex evidence earlier, structure workflows around the data, apply AI and analytics responsibly, and preserve human judgment where it matters most.

At Lineal, this is the direction we believe the industry is moving. Modern litigation support has to be data-first. The goal is not simply to move documents into review faster. The goal is to understand the data earlier, reduce unnecessary review burden, surface risk sooner, and give legal teams the visibility they need to make better decisions.

The New Role of Legal Operations

The larger takeaway from ACC Legal Operations and CLOC is that legal operations is becoming the architecture of the modern legal department. AI may be the catalyst, but the real work is broader than AI alone.

Legal operations leaders are being asked to design the systems that allow legal departments to move faster, operate with greater transparency, manage cost, improve outcomes, and adopt technology responsibly. That requires more than procurement. It requires governance. It requires change management. It requires data fluency. It requires strong relationships with internal teams, outside counsel, and service providers. And increasingly, it requires a clear point of view on where automation belongs and where human judgment must remain.

At the same time, legal departments will need to prepare for a business environment where AI is not confined to legal workflows. As AI becomes embedded across the enterprise, the records, systems, and decision trails that become relevant in litigation and investigations will become more complex. The departments that are prepared for that shift will be better positioned to manage risk, control cost, and respond with confidence when disputes arise.

The conferences made clear that legal departments are ready to move. The challenge now is to move with intention.

AI will continue to advance. Tools will improve. Law firms and vendors will bring new capabilities to market. But the most successful legal departments will be those that design an operating model around the technology rather than chasing the technology itself.

The question is no longer whether AI will be part of the corporate legal department. It will be. The better question is how legal departments will use it, govern it, measure it, and prepare for a business environment where AI is increasingly part of how decisions are made and records are created.

That is the work ahead. And it is exactly where legal operations, litigation teams, and trusted partners have the opportunity to lead.

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About Author

Marco Nasca is the Vice President of Sales at Lineal and a 2001 graduate of DePaul University College of Law. For more than two decades, he has worked at the forefront of eDiscovery and legal technology, advising corporations and law firms on the defensible application of technology in complex litigation, investigations, and regulatory matters. His work focuses on structured data, emerging technologies, and the practical implications of evolving judicial doctrine. 

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About Lineal 

Lineal is an innovative eDiscovery and legal technology solutions company that empowers law firms and corporations with modern data management and review strategies. Established in 2009, Lineal specializes in comprehensive eDiscovery services, leveraging its proprietary technology suite, Amplify™  to enhance efficiency and accuracy in handling large volumes of electronic data. With a global presence and a team of experienced professionals, Lineal is dedicated to delivering custom-tailored solutions that drive optimal legal outcomes for its clients. For more information, visit lineal.com