The conversation at July’s Consero Legal Operations Forum reflected an important shift in legal ops. The legal departments leading AI innovation are no longer asking whether AI can create value. They are focused on a much more practical challenge: how to turn AI investments into measurable business outcomes.
Across conference sessions, peer discussions, and customer meetings, legal operations leaders consistently emphasized the need to prove value, improve data quality, drive adoption, manage governance, and make smarter business decisions. Success is increasingly defined not by deploying new technology, but by operationalizing it effectively.
Is AI becoming more practical?
AI conversations have become far more practical. A year ago, most discussions centered on possibilities and future applications. Today, legal departments are implementing AI-driven capabilities in areas such as invoice review, analytics, knowledge management, contract analysis, and operational reporting.
What has changed is the criteria for success. Legal operations leaders are less interested in a list of AI features and more interested in answering important business questions:
- How does it support broader business objectives?
- Will our teams actually adopt it?
- What governance controls are required?
Many of the discussions at Consero reinforced a point I explored in a previous article, AI in Legal Ops: Why Execution Is the Real Challenge. As AI moves from experimentation to production, success depends less on identifying use cases and more on driving adoption, governance, process change, and measurable business outcomes.
What is the foundation of AI transformation?
If AI was the headline topic at the event, data was the underlying theme connecting nearly every conversation. Attendees repeatedly emphasized that better matter, invoice, contract, and knowledge data are prerequisites for future success. In fact, many participants identified data quality as a bigger obstacle than technology itself.
This concern closely aligns with themes discussed in my recent article, Would You Bet Your AI Strategy on Your Current Data? Why Governance Is Key. Many organizations expressed excitement about AI's potential while simultaneously acknowledging that inconsistent data, weak governance, and fragmented information remain significant barriers to success. simultaneously acknowledging that inconsistent data, weak governance, and fragmented information remain significant barriers to success.
Organizations cannot derive meaningful insights from incomplete, inconsistent, or poorly governed data. They also cannot confidently deploy advanced AI solutions if the underlying information lacks accuracy and structure.
Several common challenges emerged:
- Inconsistent data capture across matters and legal processes
- Fragmented knowledge repositories
- Poor governance practices
The strongest AI opportunities are emerging where organizations already have structured, accessible data. Those departments have a significant advantage because they can move more quickly from experimentation to measurable outcomes.
How is legal operations evolving?
AI is creating a new mandate for legal operations.
Across many of the conversations at Consero, legal ops leaders described a growing responsibility to do more than evaluate and implement technology. They are increasingly expected to identify the right opportunities, establish governance frameworks, drive adoption, measure outcomes, and ensure that AI investments deliver meaningful business value.
This expanded role is elevating the importance of data, analytics, and business intelligence. The organizations making the most progress are often those with the visibility needed to understand where work happens, where inefficiencies exist, and where AI can have the greatest impact.
What is the path forward?
Organizations that succeed will focus on building strong data foundations, establishing clear governance practices, measuring outcomes, driving user adoption, and connecting technology investments to business objectives.
As legal operations keeps evolving into a strategic business function, success will depend less on access to new technology and more on the ability to operationalize it effectively. The future belongs to organizations that can transform data into insight, insight into action, and action into measurable business value.
Related insights
The conversations at Consero echoed themes we have explored recently:
- AI adoption requires more than technology deployment. Read: AI in Legal Ops: Why Execution Is the Real Challenge
- Strong governance and trusted data are foundational to AI success. Read: Would You Bet Your AI Strategy on Your Current Data? Why Governance Is Key