The legal industry is in the midst of an unprecedented technology shift. According to Factor's GenAI in Legal Benchmarking Report, legal departments are pursuing both build and buy strategies simultaneously—47.5% have built internal AI interfaces/chatbots, while 40.4% have purchased specialized legal-focused AI tools.
Yet the return on these investments remains to be seen. Only 12.1% of legal teams report "leading the way" in GenAI adoption, with the majority finding themselves at average adoption levels or behind the curve. The disconnect is clear: technology acquisition alone doesn't drive transformation.
The Hidden Costs of Legal AI Implementation
Legal departments are often forced to make high-stakes technology selections in the face of an unpredictable and rapidly changing market, betting millions on platforms that may become obsolete within months or even just pivot away from the initial use case.
This dilemma carries significant risks. Over 25% of organizations we surveyed have already spent between $100,000-$500,000 on domain-specific legal AI tools, while 43.4% have upgraded existing legal tech licenses to access AI features. Perhaps more concerning, 21.2% were not sure if their existing tech stack had been upgraded to include AI features—suggesting a disconnect between investment and impact.
Beyond direct technology costs, implementation requires substantial investment in:
- Training and skills development
- Change management
- Workflow integration
- Ongoing maintenance and evolution
User Experience: The Strategic Decision Driver
The traditional build vs. buy framework focuses heavily on features, costs, and technical capabilities. But our research indicates that user experience should be the primary decision driver—especially for AI implementations.
Consider these findings from our benchmarking report:
- Only 18.9% of legal teams feel very confident using enterprise AI tools
- Almost half (47.9%) admit they "can just about get by"
- 21.3% state they "really need help" with AI
These findings reveal that legal AI is facing an adoption crisis rather than a technology crisis. The most sophisticated capabilities deliver zero value if they're not being used. Unlike conventional technology decisions where features and capabilities dominate, AI implementation success hinges on strategic alignment with how legal professionals actually work.
Evolving Past 'Build vs. Buy' Into an AI Era with Three Distinct Paths
The legal AI landscape has evolved beyond the traditional build-or-buy decision framework. Today's customizable GenAI solutions create a more nuanced approach with three distinct paths:
- Internal Development: Existing enterprise technology stacks now offer sophisticated AI capabilities accessible to both technical and non-technical team members. Creating custom solutions in-house has transformed from a compromise to a strategic advantage, allowing teams to craft precisely tailored tools that integrate seamlessly with existing systems and workflows.
- Domain-Specific Tech: The market for legal-specific AI tools continues to mature, with vendors incorporating advanced capabilities that address domain-specific challenges. While these solutions offer specialized functionality, they still require significant integration work and may become obsolete as the market rapidly evolves.
- New AI-First Service Models: Even the most sophisticated organizations can lack the capacity to keep pace with the evolving AI landscape. AI-enabled service partnerships allow organizations to avoid making risky technology bets by partnering with specialized providers who combine deep legal expertise with technical innovation. While market consolidation is inevitable, providers that combine technical innovation with deep legal expertise will deliver exceptional value through their specialized knowledge. These partnerships continuously optimize the human-AI balance for specific legal functions and deliver business outcomes rather than merely technology capabilities.
Strategic Considerations Across All Three Approaches
When evaluating which approach best fits your organization, consider these key factors:
- Build Considerations: Internal development gives maximum control over workflow integration but requires deeper UX expertise within the organization. Organizations building their own solutions must consider whether they have the design capabilities to create experiences that legal professionals will actually use.
- Buy Considerations: Specialized vendors may offer refined interfaces but with less customization to your specific processes. Evaluating vendor solutions should include assessment of their adaptability to your team's existing workflows and interface preferences. This approach may require ongoing investment as technology evolves.
- New AI-First Service Models: This approach combines discovery-led experimentation with legal expertise to deliver practical solutions at speed. Organizations should evaluate potential partners based on their domain expertise, ability to blend technology with practical legal knowledge, and approach to continuous improvement. The best partnerships maintain humans at the center while leveraging AI to augment capabilities, not replace expertise. Unlike other approaches, service model success is measured by business outcomes rather than technology implementation milestones.
The key question is not just whether a solution has the right features, but whether your organization has the right capabilities to deliver the necessary user experience through either path.
Crossing the IT-Legal Collaboration Divide
One of the most striking findings from Factor’s recent AI adoption benchmarking report is that 24.5% of respondents rated IT 10/10 for eagerness to help with legal AI tools—a dramatic shift from historical patterns where legal was deprioritized as a cost center.
Yet despite this unprecedented willingness to collaborate, 33.3% of respondents report minimal or non-existent collaboration with IT on AI implementation. This represents a significant missed opportunity.
Organizations achieving the highest ROI are capitalizing on this new alignment by:
- Establishing dedicated cross-functional teams
- Creating formal collaboration mechanisms
- Developing shared understanding of legal workflows and needs
- Building legal-IT "translation" capabilities
The Path Forward: Value-Driven Decision Making
Whether building, buying or partnering, successful organizations focus on value rather than novelty. The benchmarking data shows that organizations achieving the highest ROI consistently prioritize high impact use cases addressing specific pain points rather than implementing AI for its own sake.
This value-driven approach should include:
- Mapping current workflows to identify friction points and opportunities
- Evaluating user readiness and capabilities to determine appropriate interfaces
- Prioritizing use cases based on business impact and implementation feasibility
- Establishing clear success metrics tied to business outcomes
- Creating feedback loops to drive continuous improvement
The data validates a simple truth: in the rapidly evolving GenAI landscape, those who put user experience at the center of their AI approach will see substantially higher returns on their investments.
David Mainiero is VP, AI Enablement & Legal Transformation at Factor. Join him at the CLOC Global Institute on May 6th at 8am for a panel discussion "Beyond AI Implementation: Leveraging UX to Accelerate Adoption".
