Morgan & Morgan, the self-described largest injury law firm in the United States, plans to invest $1 billion in artificial intelligence and legal technology over the next decade. The firm has already spent $300 million developing its proprietary AI system, MX2, and intends to market the platform to other law firms, signaling a major capital shift in how plaintiffs' litigation is resourced and fought.
The move has drawn attention from insurance defense lawyers who are themselves adopting similar tools to counter plaintiffs' tactics. Paul Lopez, an insurance attorney and chief operating officer with Tripp Scott in Florida, described the technological escalation as mutual. "It's a two-way street. Defense firms also are using AI to counter plaintiffs' actions," Lopez said. "AI can make good, hard-working lawyers better and more efficient."
How the AI is being used in courtrooms
Morgan & Morgan's MX2 platform extracts medical records, locates police reports, generates case documents and demand letters, identifies patterns, and assists with trial preparation. The system has nearly 5,000 regular users across the firm's roster of more than 1,100 lawyers. Insurance defense attorneys report seeing the technology deployed during jury selection, where it rapidly surfaces potential jurors' social media activity, employment history, education, and property ownership.
Nick Kosiavelon, a Massachusetts insurance lawyer, witnessed this firsthand while opposing Morgan & Morgan in a brain-injury case. He said the technology provided deep background on the jury pool in under an hour. But speed did not translate into results. Jurors returned an award that was one-tenth of what the plaintiffs had requested. The outcome underscores a reality that both sides are confronting: AI can accelerate preparation, but it does not guarantee courtroom victories.
Defense firms respond with their own investments
Large defense firms are committing significant capital to AI, though not yet at Morgan & Morgan's scale. Chicago-based Kirkland & Ellis said in May it will spend $500 million over three years to develop an AI platform. Other firms are using the technology to sift through vast document sets, evaluate arguments, and vet jurors in injury and claims litigation.
Morgan & Morgan founder John Morgan argued that firms relying on hourly billing face greater disruption from AI adoption. The implication is clear: efficiency gains from automation threaten the billable-hour model that many insurance defense practices depend on.
The technology's growing pains
AI tools in legal settings remain prone to error. Platforms continue to hallucinate case citations and legislative references that do not exist. Last year, a federal judge in Wyoming sanctioned Morgan & Morgan lawyers for filing a motion that cited eight nonexistent cases, some apparently generated by AI. In May, the Florida Supreme Court introduced rules requiring lawyers to certify that citations in filings are real and accurately referenced.
Lopez cautioned that AI systems sometimes aim to please. "We have to be careful," he said, noting that the technology can offer answers it believes a lawyer wants to hear rather than what the law supports.
Why this matters for insurance professionals
For insurance claims handlers, adjusters, and defense counsel, the billion-dollar commitment from the country's largest injury firm changes the economics of litigation. Plaintiffs' lawyers with AI tools can generate demand letters, medical chronologies, and case filings faster and at lower internal cost. This may increase claim volume and pressure settlement timelines. At the same time, defense-side investment in AI for Insurance is creating countermeasures that can surface inconsistencies in claims and accelerate document review. Professionals who understand how these tools function - and where they fail - will be better positioned to assess the real exposure behind an AI-assisted demand package. For those in legal departments, familiarity with AI for Legal applications is becoming a core competency, not a specialization.
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