You Are Already Using AI. The Question Is Whether You Are Using It Well.

A keynote session from the MastersAI x TechnoCat Conference, Chicago, April 16, 2026.

Cat Casey has spent 20 years telling the legal profession that AI was coming. Three and a half years ago, it arrived. Her opening keynote in Chicago was less a warning than an orientation: a fast, direct briefing on where AI stands today and what legal professionals need to do about it.

Casey opened with a number that reframes the conversation entirely. It took the internet 20 years to reach 100 million users. Facebook took four and a half years. ChatGPT reached that milestone in 62 days. “We are moving at a speed much faster than we have in prior tech transformations,” she told the audience. “And we are accelerating that.” The point was not to generate anxiety but to establish urgency: what looks like a wave is already a permanent condition.

She pushed back against the framing that AI is a hype bubble waiting to burst. Unlike the metaverse or Web3, generative AI skipped the trough of disillusionment and moved directly into production. Her explanation: the technology is not new. AI has existed since 1956, weathered multiple winters, and arrived in 2022 with 70 years of foundational investment behind it. The consumer moment was not a beginning. It was a tipping point.

“Trust, verify, and maybe even verify before you trust at this point. That does not mean do not use it. It means supervise the tech.”

The session covered the AI spectrum from deterministic tools like search engines and data visualization platforms to generative systems that create rather than find. Casey was deliberate in drawing that line. Generative AI introduces a different risk profile for legal professionals, one that demands a different kind of judgment. Hallucinations remain a real concern, though she noted the nature of the problem is evolving. Outright fabricated cases are becoming less common. Subtler errors are becoming more common: the wrong district, a precedent misapplied across practice areas. Catching those requires the kind of domain expertise that no model can replicate.

She also addressed deepfakes and what she called the liar’s dividend: as AI-generated content becomes more sophisticated, the instinct to distrust even authentic evidence grows. For litigators, that has direct evidentiary implications. Body camera footage, CCTV recordings, and other visual evidence are increasingly subject to authenticity challenges regardless of whether AI was involved in their creation.

Casey closed with what may be the most useful reframe of the day: lawyers are unusually well-equipped for the AI era. The precision with language, the ability to structure an argument, the IRAC logic that law school hammers in from day one. These are exactly the skills that make someone effective at prompting. “If we can master that basic entry point,” she said, “we leapfrog even STEM experts.”

Key Takeaways

• Generative AI adoption has no historical precedent for speed. The legal profession is not catching up to a trend. It is operating inside one.
• AI is a spectrum. Deterministic tools and generative tools carry different risk profiles and require different guidance for clients and organizations.
• Hallucinations are evolving. The risk is less about fabricated cases and more about subtle misapplication of real ones. Domain expertise is the only reliable check.
• The liar’s dividend means authenticity challenges are growing for all visual evidence, not just AI-generated content.
• Lawyers’ precision with language is a competitive advantage in the AI era, not a liability. Prompting is a skill set the profession is already built for.

Conference Coverage: Chicago, April 16, 2026