The AI Spend Trap: Join eBrevia and Platforum9 for a Practical Conversation About Buying, Building and Measuring Legal AI
Today, most law firms and corporate legal departments have access to multiple AI tools. Microsoft Copilot. ChatGPT Enterprise. One or more legal AI platforms. CLM systems. Document management. Legal research platforms. Workflow software.
The critical post-adoption question: Which AI is actually worth paying for?
Join eBrevia and Platforum9 for an online discussion exploring how legal teams can make better AI investment decisions as the market matures.
The AI Spend Trap: What Legal Teams Should Buy, Build and Stop Paying For
The session will be co-moderated by Megan Mulligan, Growth & Partners Lead at eBrevia, with Adam Nguyen, eBrevia's Co-founder and CEO, leading the discussion.
Rather than focusing on product demonstrations, we'll examine the practical decisions legal teams are making today as they balance growing pressure to adopt AI with increasing scrutiny over budgets and return on investment.
Legal AI Conversations Have Shifted
Legal AI has evolved remarkably quickly. Deloitte recently reported that 61% of legal departments are now deploying AI, with only 2% reporting no AI adoption at all. Agentic AI pilots are already becoming increasingly common as organizations move beyond experimentation into operational use. Investment in legal AI continues to accelerate, with billions of dollars flowing into new companies and products.
More software doesn't automatically equate to more value, however, and lawyers continue to report familiar frustrations:
Switching between disconnected systems
Duplicate work across multiple platforms
Low user adoption
Difficulty driving organizational change
Unclear return on investment
Many legal leaders are now finding themselves managing overlapping technologies without a clear strategy for which ones truly deserve long-term investment.
Buy Less. Solve More.
The most valuable legal AI is practical, and typically does four things well:
Saves lawyers meaningful time every day
Fits naturally into existing workflows
Leverages the organization's own knowledge and precedents
Produces measurable business outcomes
One of the simplest ways to evaluate any AI investment is to ask: What measurable problem does this solve that isn't already being solved today?
If the answer isn't clear, it's worth questioning whether another platform is the right investment.
Should You Build Rather than Buy?
Another emerging trend is the growing interest in building AI tools internally.
Several large organizations have publicly discussed developing their own legal AI capabilities rather than relying exclusively on vendors. Recent announcements from major law firms illustrate how quickly this conversation is evolving.
Building internally can make sense in some situations, but it comes with significant challenges.
Many organizations underestimate the effort required to define requirements, maintain internal expertise and continue investing as projects evolve. Once substantial time and money have been committed, it can become difficult to step away even if the expected value never materializes.
Instead of trying to build foundational AI models, many organizations may see greater returns by building assets around their own expertise, including:
Internal playbooks
Prompt libraries
Workflow automations
Knowledge repositories
A firm's competitive advantage isn't the AI model; it's the institutional knowledge behind it.
Learning From What Legal Teams Are Experiencing
The discussion will also draw on real conversations we've had with law firms and corporate legal departments over the past year.
Many organizations are exploring whether they should continue purchasing specialized AI products or develop solutions internally. Some face pressure from executive leadership to invest in AI while simultaneously being expected to demonstrate immediate productivity gains. Others are rethinking traditional technology investments altogether, looking for faster, more flexible approaches that deliver value without lengthy implementation projects.
Such challenges are common across the industry.
Who Should Attend?
This discussion is intended for general counsel, legal operations leaders, innovation teams and law firm professionals responsible for evaluating AI investments.
Whether you're considering another legal AI platform, debating whether to build internally, or trying to make better use of the technology you already own, the session will offer practical perspectives drawn from conversations with legal teams facing these same decisions every day.
We'll also share how organizations are approaching AI strategy more broadly, from evaluating return on investment to identifying where technology can deliver measurable business value.
The AI Spend Trap: What Legal Teams Should Buy, Build and Stop Paying For
Date: Thursday, July 23, 2026
Time: 2:00 PM BST (London)
Format: Online webinar via Platforum9
Join Megan Mulligan, Growth & Partnerships Lead at eBrevia, and Adam Nguyen, Co-founder and CEO of eBrevia, for a practical discussion on how legal teams can make smarter AI investment decisions, evaluate ROI, and decide what to buy, what to build, and where to stop spending.
Register here: Reserve your spot on Platforum9
About eBrevia
Established in 2011 and trusted by some of the world’s most prestigious companies, eBrevia is a leader in AI contract analysis and management with clients in the US, EMEA, and APAC. For more than a decade, eBrevia serves law firms, corporations, audit/consulting companies, and financial institutions, such as Baker McKenzie, Norton Rose Fulbright, Kroll, SAP, Intel, PwC, EY, and MUFG
