“The only thing worse than the absence of data is bad data,” he told the room. “You can feed AI confident wrong answers if you haven’t done the correct analysis on your measurement system first.”
Smoke was talking about battery cells. But swap a few nouns and he could have been describing the brief on your desk, the intake summary a new tool just generated, or the practice-area page an AI wrote for your website last week. The lesson the manufacturing world learned the hard way is one the legal profession is now learning in real time: a tool is only as trustworthy as the data and the process feeding it. We have written about the sharp end of that problem in The Hallucination Plateau, where AI-fabricated citations are now a standing sanctions risk. This is the upstream version of the same story.
Why a Battery Line and a Law Firm Have the Same AI Problem
In battery manufacturing, a process deviation is not a cosmetic flaw. It can degrade performance, cause a loss of function, or create a genuine safety failure. Smoke put the stakes in plain terms. “A quality slip in automotive manufacturing leads to a quality escape,” he said. “But in battery manufacturing, the consequences have a much higher order of magnitude.”
A law firm operates under the same asymmetry. A typo in a marketing email is a quality escape. A fabricated citation in a filing, a conflict check an AI tool quietly mishandles, or a client-intake message that promises something the firm cannot deliver — those are a much higher order of magnitude. The output of an AI tool always looks finished. That polish is exactly the problem. It looks like a brief. The citations look like citations. Nobody pulls the case.
The point is not that AI is dangerous. The point is that confidence is not accuracy, and an AI tool will hand you a confident wrong answer with the same fluency it hands you a correct one.
The Plant Builds Quality Gates. Your Firm Should Too.
Smoke described how the facility manages risk: a layered approach of interlocked equipment systems and electrical testing, with each step acting as a process gate before any product leaves the building. Nothing advances until it clears the gate. Quality is not something an inspector remembers to check at the end. It is built into the workflow.
That structural discipline is exactly what the bar now expects of lawyers. In Formal Opinion 512, issued in July 2024, the American Bar Association made clear that the duty of competence under Model Rule 1.1 requires lawyers to understand the limits of the generative AI tools they use and to independently verify the output — uncritical reliance on AI can itself be a competence violation. (The full opinion is here.)
In the law firm sites we have audited, the firms that get into trouble are rarely the ones that adopted AI carelessly. They are the ones that adopted it without changing a single downstream review process. The technology slipped into the workflow. The verification step did not get added.
A defensible process looks structural, not motivational. Every AI-generated citation gets pulled. Every quote gets sourced. The person who drafted the document is not the person who verifies it. The verification step gets its own slot on the calendar, not the final twenty minutes before a filing deadline. Good intentions are not a quality gate. A process is.
Move From Reactive to Proactive — Before the Filing, Not After
Smoke’s larger argument was about where data actually earns its keep. Connected systems, he explained, let engineers spot “parameter drift” before it turns into a performance problem — moving a plant from reactive problem-solving toward proactive process management. Catch the trend early, and you fix a setting. Catch it late, and you scrap a batch.
For a law firm, proactive means catching the hallucinated case, the wrong jurisdiction, or the stale statute at the draft stage — not after opposing counsel flags it or a judge writes it into an opinion. The cost of catching an AI error early is a few minutes. The cost of catching it late is a public sanction and a search result that pairs your firm’s name with “fabricated authority” for the next decade. The dollar amount of a fine is recoverable. The reputation cost is not — and repairing it is a public relations problem long after the docket has moved on.
The same logic applies to client-facing AI. Before you put a chatbot or an AI receptionist in front of prospective clients, you need to know what it will say when nobody is watching. We walked through the questions worth asking first in Should Your Law Firm Build an AI Twin?. Proactive review is cheaper than a retraction.
Flexibility Is a Feature, Not a Liability
One more thing Smoke said is worth borrowing. Rather than building fully dedicated production lines around a single product, the plant deliberately designed for adaptability — changeable tooling, programmable controls, adjustable fixtures — because the underlying technology is still evolving fast.
The same caution applies to your AI stack. The tool you standardize on this year may be eclipsed next year. Do not hard-wire your entire intake, drafting, or client-communication process around one vendor you cannot swap. Build a process that owns the standard, and let the tools plug into it. When the better tool arrives — and in this market, it will — you want to change the tool without rebuilding the firm.
The Bottom Line
AI is only as good as the data and the process behind it. A small firm does not need to fear the technology — it needs to build the same kind of quality gates a battery plant builds: a verification step owned by a second person, a discipline of catching errors at the draft stage rather than the filing stage, and an AI stack flexible enough to swap when something better comes along. The speed AI offers is real. The speed is also exactly where the trap lives.
When the Business Law unit gets taught at Greenville Technical College, the recurring lesson is that procedural discipline is what separates competent practice from sanctionable practice. The medium changes. The principle does not. A factory engineer in Greer arrived at the same conclusion about batteries. It travels surprisingly well to a law office.
The same “garbage in, garbage out” rule now governs how your firm shows up in search. Google’s own people-first content guidance rewards original, well-sourced, demonstrably expert content and demotes thin material mass-produced to game rankings — which means an AI-generated practice-area page with no verification behind it is both an ethics risk and a ranking risk. If your firm wants help building a content and communication process that holds up to client scrutiny, the bar’s expectations, and that E-E-A-T standard, Toppe Consulting’s law firm content writing, SEO, website development, and public relations practices work with attorneys across South Carolina.
Sources
This article draws on the following sources.
Smoke, Clay. Remarks delivered as Manufacturing Engineering Manager at a Minds Behind the Machines event, commercial EV battery facility, Greer, South Carolina. Primary source for the quotations on data quality, quality gates, proactive process management, and design flexibility.
American Bar Association, Standing Committee on Ethics and Professional Responsibility. “Formal Opinion 512: Generative Artificial Intelligence Tools,” July 29, 2024. Announcement | Full opinion (PDF). Cited for the duty of competence (Model Rule 1.1) and the requirement to independently verify AI output.
Google Search Central. “Creating Helpful, Reliable, People-First Content.” developers.google.com. Cited for Google’s E-E-A-T framework and its treatment of automated and AI-generated content.
Disclaimer
About the Author
Jim Toppe is the founder of Toppe Consulting, a digital marketing agency specializing in law firms. He holds a Master of Science in Management from Clemson University and teaches Business Law and Marketing at Greenville Technical College. Jim also serves as publisher and editor for South Carolina Manufacturing, a digital magazine. His background combines legal knowledge with digital marketing expertise to help attorneys grow their practices through compliant, results-driven strategies.
