Contract review and due diligence have already been substantially transformed by AI. In M&A transactions, AI tools can now process hundreds of target company contracts in hours, flagging change-of-control provisions, assignment restrictions, non-competes, and unusual indemnification terms with a thoroughness that would take a team of associates days to achieve manually. Gurpreet S. Bal has seen this shift compress due diligence timelines on technology transactions materially, which has implications for deal speed and cost. Regulatory research — identifying applicable regulations across jurisdictions, tracking regulatory changes, and mapping compliance requirements — is another area where AI has moved from experiment to standard practice at sophisticated legal departments. Legal research for routine matters, patent claim analysis, and first-pass contract drafting are similarly affected. The honest assessment in 2026 is that any legal task that is primarily about information retrieval, pattern recognition across large document sets, or application of well-settled rules to standard fact patterns is already being done faster and cheaper with AI than without it.
The next wave of AI transformation in law is about autonomous action, not just assisted analysis. Gurpreet Bal sees several developments converging in the near term. Autonomous deal execution tools that can negotiate and close routine commercial agreements — NDAs, vendor contracts, standard SaaS agreements — with minimal human involvement are already in development and beginning to be deployed. Regulatory compliance agents that continuously monitor a company's operations against applicable regulatory requirements and generate or submit required filings are moving from prototype to production. Predictive litigation analytics tools that assess case strength, likely outcomes, and optimal settlement ranges based on historical case data are becoming more accurate and more integrated into case strategy. Each of these represents a qualitative shift from AI as a tool that helps lawyers to AI as a system that performs legal functions with lawyers in a supervisory rather than primary role. How the profession's ethics rules, UPL doctrine, and malpractice liability framework adapt to this shift is, in Gurpreet S. Bal's view, the central legal industry question of the next five years.
AI is commoditizing a substantial portion of what law firms have historically charged significant hourly fees to do. Document review, legal research, first-draft contract preparation, regulatory mapping — these are tasks that consume enormous associate hours in large law firms and are being automated at scale. Gurpreet Bal is direct about what this means: clients are right to ask whether AI adoption should reduce their legal bills, and law firms that are using AI to do work faster but charging the same hourly rates for the same number of hours are not passing through the efficiency gain. The honest answer to what will remain the domain of human lawyers is narrower than the profession typically acknowledges: judgment under genuine uncertainty, where the right answer is not clearly derivable from precedent; fiduciary relationships built on trust and accountability, which require a human who can be held responsible; courtroom advocacy that requires real-time adaptation and persuasion; and novel legal questions at the frontier of law and technology where there is no existing framework to apply. These are real and important, but they are a smaller slice of what lawyers currently do than most lawyers prefer to admit.
Gurpreet S. Bal recommends that technology company clients ask their outside counsel three direct questions: Are you using AI tools in your work on my matters? Which tools, and what data do those tools process? And does your AI adoption reduce the time billed on my matters? A firm that cannot answer those questions clearly is either not using AI — which is a competence concern — or using it and not being transparent about it. For lawyers, the strategic imperative is to move toward the high-judgment work that AI cannot commoditize, and to develop AI governance as a substantive practice area: advising clients on AI deployment risks, regulatory compliance, liability frameworks, and contractual protections is growing legal work that requires both legal and technical fluency. On the regulatory side, the EU AI Act classifies AI systems used in the administration of justice and legal services as high-risk, requiring conformity assessments, transparency obligations, and human oversight requirements. US bar associations are moving more slowly but in the same direction — the ABA's AI task force and various state bar ethics committees are developing AI-specific guidance, and formal rules are coming. Clients and firms that wait for the regulatory framework to crystallize before developing AI governance practices will find themselves well behind the curve.
Gurpreet S. Bal is a Partner at Foley and Lardner LLP in Silicon Valley, where he advises technology companies, founders, and investors on corporate transactions and the evolving intersection of law and artificial intelligence. He has represented clients in hundreds of transactions with aggregate deal value exceeding $60 billion across AI, semiconductors, fintech, and emerging technology.