Beyond Copilots: Taylor Galusha On Automating Legal Work
- cosmonauts
- 13 minutes ago
- 5 min read
Disclaimer: The views and opinions expressed in this blog post are Taylor Galusha’s and do not reflect those of his employer, Chime. He is sharing his personal perspective and is not speaking on behalf of the company.
AI can already draft, synthesize, organize, and surface information at extraordinary speed. But periods of technological acceleration have never rewarded expertise alone.
Both specialists and beginners can misread transformation when familiar frameworks stop behaving predictably.
In our latest interview with Taylor Galusha, Lead Privacy & AI Counsel at Chime, we explore the distinction between AI-assisted legal work and AI-automated legal work, and the enduring role of professional judgment.
That thinking will shape Taylor’s upcoming panel contribution during In-House Day at Legal Innovators California 2026: “Automating Away The Pain.”
A practical conversation on automation, workflow design, data curation, and how legal teams decide whether to buy, build, or combine solutions already driving real impact in practice.
Before meeting Taylor live in San Francisco this June, we invite you to read the interview below and step into the conversation early.
What does a typical week look like for you as an in-house lawyer working across legal, privacy, and AI?
There is really no such thing as a typical week, which is one of the reasons in-house work is both challenging and fun.
My priorities are largely driven by what the business is building, launching, or testing. Chime is a very product-oriented company, so when a new initiative involves personal information, AI, or both, I am often pulled in to help the team move quickly while managing the legal, privacy, and governance risks.
That means the foundation matters a lot. You need privacy and AI governance programs that are standardized, practical, and easy for the business to engage with. The more you can simplify, template, and automate the repeatable parts of the work, the more capacity you create for the judgment-based fire drills that inevitably come up.
In-house counsel are essentially on retainer for the business. You need to be responsive to the urgent issues, but you also need enough structure in place so every new question does not become a fire drill.
To what extent is technology the main driver of innovation, compared to cultural or organizational change?
Technology often creates the possibility for innovation, but culture determines how quickly and effectively that innovation actually happens.
AI is a good example. The technology is already changing how legal teams research, draft, and organize information. But whether a company actually benefits from that depends on its appetite for change, its risk tolerance, and its technical foundation.
Older organizations with legacy systems and rigid processes may struggle to adopt new technology, even when the technology itself is powerful. More agile organizations can move faster, but they still need governance and accountability.
So I do think technology is a major driver of innovation. But culture and organizational design determine whether that technology becomes a real advantage or just another tool people are afraid to use.
How do you maintain quality control and professional accountability when AI is doing a significant portion of the drafting or research?
The most important point is that the lawyer is still the professional. AI can assist with drafting, research, synthesis, and issue spotting, but it does not replace professional judgment.
If I use AI to help analyze a privacy or AI governance question, I still need to know whether the output is complete, accurate, and useful. That requires substantive expertise. You cannot responsibly supervise AI-generated legal work in an area you do not understand.
Quality control also depends on how you use the tool. You need to point the AI toward the right sources, jurisdictions, facts, and legal framework. In that sense, using AI well is not that different from giving instructions to a junior lawyer. The quality of the output depends heavily on the quality of the direction.
So for me, accountability comes down to two things: first, maintaining your own professional judgment; and second, being disciplined about how you prompt, scope, review, and validate the output. AI can make lawyers more efficient, but it does not eliminate the lawyer’s responsibility for the final work product.
What does “AI-assisted legal work” mean to you versus “AI-automated legal work”? Do you draw a distinction?
Yes, I draw a very clear distinction.
AI-assisted legal work is real, useful, and already here. It means using AI as a tool to help lawyers deliver faster, clearer, and more effective advice. That could include summarizing materials, preparing first drafts, organizing research, comparing documents, or helping a lawyer think through an issue.
AI-automated legal work is different. Legal work requires judgment, professional responsibility, and accountability. I do not think we should describe core legal judgment as something that can simply be automated away.
That said, a lot of what lawyers do is not actually legal judgment. It is administrative work around legal work: tracking, formatting, researching, routing, billing, summarizing, searching, organizing, and documenting. Those are exactly the kinds of tasks we should be automating where we can.
The goal is not to automate away the lawyer. The goal is to automate away the pain points that keep lawyers from spending more time on the work that actually requires legal judgment.
What excites you most about speaking at Legal Innovators California?
I am excited to be in a room with people who are thinking seriously and practically about how technology can make legal work better.
My panel is called Automating Away the Pain, which is exactly the right framing. There is so much work in the legal profession that is necessary but not especially legal in nature. Lawyers spend a surprising amount of time on administrative tasks, process management, and repetitive work that does not require a law degree.
My first job after undergrad was as an administrative assistant, so I have a lot of respect for operational work. I also know the difference between work that requires legal judgment and work that simply needs to get done. The more we can automate or streamline the latter, the more time lawyers can spend on the highest-value issues for their clients and companies.
I am also excited to be around people who are not afraid of AI. Lawyers have always had to adapt to new tools, whether it was email, search engines, document management systems, or now generative AI. The right response is not fear. It is thoughtful adoption, clear guardrails, and a continued commitment to professional responsibility.
Used well, AI can help us become better lawyers.
Looking ahead, how do you think the balance between human expertise and automated systems will evolve in legal work?
In the near term, I think we will see automated systems take on more of the research, drafting, review, and administrative work that currently consumes a significant amount of lawyers’ time. Human lawyers will still be responsible for judgment, risk calibration, client counseling, and accountability.
Over a longer horizon, I think AI will become very strong at the part of legal work that many lawyers currently view as central to their role: finding the relevant law, synthesizing it, and applying it to a fact pattern. AI will be able to process far more source material than any one human can hold in their head.
That does not mean human expertise becomes irrelevant. It means the lawyer’s role shifts. The highest-value lawyers will be the ones who can ask the right questions, understand the business context, identify the true gray areas, and make sound judgment calls where the answer is not obvious.
Legal work will become less about manually finding every relevant source and more about directing, validating, and applying legal analysis in a practical way.
The legal industry has become saturated with polished narratives, ambitious promises, and AI platforms positioned as the definitive answer to legal complexity.
At Legal Innovators California, Taylor will examine where automation is generating measurable enterprise value, where industry optimism has outpaced practical reality, and why disciplined implementation matters far more than innovation theater.
History shows that specialists fail just as often as beginners when the world shifts quickly. Join us in San Francisco this month and prove you are the exception.
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