ANALYSIS: Why AI Return on Investment in Legal Will Lag in 2026

Most in-house attorneys say their organizations are already using generative AI, according to a recent Bloomberg Law survey. Yet despite growing enthusiasm for and investment in AI, measurable returns remain to be seen.

Across in-house teams, generative AI tools are being piloted for a variety of different legal workflow enhancements, while vendors are embedding AI capabilities into existing platforms. But implementation alone doesn’t equal transformation. Valuable ROI depends on deep, consistent adoption and strong data foundations.

In 2026, the gap between investment and impact will reflect uneven usage of GenAI tools and uneven adoption across legal departments, combined with underdeveloped data infrastructure rather than technological shortcomings. Thus, legal departments will focus less on proving AI’s value and more on building the systems, consistency, and confidence needed to measure it accurately.

AI in Pilot Mode

AI adoption within corporate legal teams remains fragmented. Many departments are still in pilot mode, testing tools in isolated practice areas or with small user groups. While these pilots highlight potential efficiencies, few have been implemented organization-wide. Until AI becomes embedded in everyday workflows, the data volume and quality needed to assess ROI will remain limited.

Only 23% of in-house lawyers who responded to Bloomberg Law’s most recent State of Practice survey use AI tools daily, while 27% haven’t used them in the past six months. This uneven engagement suggests that adoption is still surface-level rather than systemic, resulting in scattered performance gains that are difficult to quantify or translate into meaningful metrics.

Among in-house professionals who reported using AI at least a few times a month, one-third say it saves them less than 30 minutes a day, while 22% report time savings of 30 minutes to an hour. These marginal efficiency gains underscore a deeper challenge: Expectations for AI’s transformative potential remain out of sync with its current stage of maturity for legal practice.

For organizations that haven’t yet adopted generative AI as of late April of this year, both in-house and law firm attorneys said that the top reasons include: unreliable or incorrect outputs (49%), ethical concerns (49%), security risks (48%), and the lack of a clear business need (43%). Another 32% point to the immaturity of existing AI models as a limiting factor.

Together, these findings highlight a fundamental truth that despite rapid innovation, generative AI tools for legal practice still require significant oversight, which often offsets the efficiency gains they promise.

Executives frequently anticipate measurable results within a single budget cycle. Yet those expectations are rarely grounded in realistic timelines or well-defined success metrics. Without a consensus on what AI is meant to achieve—whether faster contracting, lower legal spend, or fewer escalations—departments end up with inconsistent AI adoption and unclear ROI benchmarks.

Adoption, after all, isn’t a one-time rollout; it’s an evolving process that depends on culture, trust, and workflow integration. Until AI becomes universally embedded across teams and practice areas, its measurable impact on legal departments will remain limited.

The Hidden Prerequisite: Data Readiness

Even with widespread adoption across legal teams, AI’s ROI can’t be accurately measured without strong data foundations. Most corporate legal departments weren’t designed for quantitative analysis. Many still rely on manual reporting, fragmented systems, and inconsistent metrics for tracking matters, turnaround times, and outside counsel spend.

Without clean, unified baselines, comparing performance before and after AI implementation becomes nearly impossible. The result is that AI’s impact often appears weaker than it truly is.

Throughout 2026, legal departments will continue investing heavily in data quality, standardization, and integration. They will focus on cleaning legacy datasets, establishing consistent taxonomies, and connecting disparate systems to create a single source of truth. These foundational efforts may postpone short-term ROI but are critical for building long-term credibility and measurable outcomes.

Effective AI strategies in legal operations depend on structured, high-quality data that enables continuous measurement. Until that structure is in place, ROI will remain more aspirational than demonstrable.

2026: The Year of Foundations, Not Payoffs

The coming year will be about creating the conditions for future value rather than about capturing it immediately. Legal operations teams should concentrate on four key areas:

• Measuring adoption by tracking usage, frequency, and workflow integration.
• Building baselines for matter volume, turnaround time, and spend.
• Integrating data across matter management, document, and billing systems.
• Aligning metrics with enterprise goals such as risk mitigation and decision support.

These initiatives won’t generate dramatic ROI figures in 2026, but they will produce something more critical: a credible framework for long-term measurement.

Rethinking ROI

Traditional ROI measures like hours saved or costs reduced tell only part of the story. The real impact of AI lies in how it changes legal’s role in the business. AI improves risk detection, enhances decision-making, and creates capacity for strategic work. These results are harder to quantify but ultimately more valuable.

In 2026, forward-looking legal departments will begin transitioning from measuring “efficiency saved” to “value created.” This includes risk avoidance, better decision accuracy, and the redeployment of talent to higher-value activities. Once adoption and data readiness mature, these strategic outcomes will form the basis of measurable ROI.

Looking Ahead

2026 will be a foundational year, more about building than boasting. Legal departments will refine adoption strategies, strengthen data infrastructure, and align leadership expectations around realistic timelines for achieving any measurable ROI. These efforts may not deliver immediate payoffs, but they’ll lay the groundwork for long-term, demonstrable success.

After 2026, the focus will shift from experimentation to evidence. Departments that have invested in consistent workflows and clean data will finally be positioned to quantify AI’s impact, translating early enthusiasm into verifiable efficiency, savings, and strategic value.

Access additional analyses from our Bloomberg Law 2026 series here, covering trends in Litigation, Corporations & Transactions, Executive Orders & Authority, and Artificial Intelligence.

Bloomberg Law subscribers can find related content on our In-House Counsel resource and our Surveys, Reports & Data Analysis and AI for Legal Ops & Firm Management pages.

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