Adam Nguyen, CEO and Co-Founder of eBrevia, has spent more than a decade at the forefront of legal AI, founding the contract intelligence company in 2011, years before generative AI transformed the legal technology market. After selling the business in 2018 and reacquiring it in 2023, Nguyen has worked with law firms and corporate legal teams across multiple generations of AI adoption. During the session, he explained that this experience has shaped his current focus: helping organisations make smarter AI investment decisions based on business outcomes rather than technology hype.
Session Overview
As AI becomes a standard part of legal practice, Nguyen argued that the conversation has shifted from whether organisations should adopt AI to how they should invest wisely. Many legal departments already operate multiple AI platforms alongside contract management, document management and research systems, yet lawyers continue to experience duplicated work, fragmented workflows and uncertain returns on investment. Rather than buying more technology, organisations should first identify the problems they are actually trying to solve.
A central theme throughout the discussion was that process improvement should come before automation. Nguyen introduced a simple framework: eliminate unnecessary work, simplify what remains, standardise repeatable processes and only then automate. Automating poor processes simply accelerates inefficiency. He encouraged legal leaders to challenge longstanding practices by asking whether every approval, review stage or report genuinely adds value. He also stressed that AI should be evaluated on measurable business outcomes rather than impressive features, reminding attendees that many products now rely on the same underlying foundation models.
The session also examined the economics of AI adoption. Nguyen warned that licence fees represent only a fraction of the total cost, with implementation, integration, maintenance, governance and ongoing support often becoming the largest long-term expenses. While some organisations are exploring building their own AI capabilities, he cautioned that maintaining internal solutions requires continuous investment and expertise. Instead of pursuing large-scale transformation projects, he recommended starting with small, high-value use cases, measuring results carefully and scaling only after clear value has been demonstrated. Throughout the discussion, Nguyen emphasised that successful AI strategies are driven by disciplined decision-making rather than fear of missing out.
Key Takeaways
- Eliminate unnecessary work before automating processes. AI should improve workflows, not accelerate inefficient ones.
- Buy technology based on measurable business outcomes rather than attractive AI features or product demonstrations.
- Evaluate the full cost of AI, including implementation, integration, maintenance and long-term support, rather than focusing solely on licence fees or token pricing.
- Purpose-built legal AI solutions continue to provide value where consistency, scale, governance and quality control are critical.
- Organisations choosing to build AI internally should treat it as an ongoing product investment, not a one-off project.
- Start with focused, high-impact use cases, prove measurable ROI and expand AI adoption incrementally rather than pursuing large-scale transformation from the outset.
