Recent news about LinkedIn's crackdown on low-quality AI content, alongside broader concerns about authenticity in hiring, points to the same lesson for professional-services firms: AI can help, but only when it's used in controlled workflows with clear review standards.
Why this news matters to professional-services firms
LinkedIn's new reporting tool for low-quality AI content shows that audiences are getting less tolerant of generic, obviously automated material. For law and accounting firms, that is a direct signal that credibility now depends on how AI is used, not just whether it is used.
At the same time, employers are already using AI in hiring while becoming more skeptical of AI-generated candidate materials. That tension reflects a wider market reality: firms want the speed of automation, but they still expect authenticity and judgment.
Custom AI beats generic AI content
For a firm, the goal should not be to publish more content just because AI makes that possible. The goal is to build workflows that support real expertise, such as drafting outlines, summarizing source material, routing content for review, and standardizing tone before anything goes live.
That is where custom AI is more useful than off-the-shelf chat tools. A custom workflow can be designed around your firm's approved language, practice areas, risk tolerance, and review process so the final output sounds like your firm and not like AI slop.
Agentic workflows should reduce risk, not just save time
Agentic workflows are most valuable when they handle repetitive steps that are easy to standardize, such as intake triage, document summarization, internal research prep, or first-pass drafting. But these systems should still stop short of publishing, sending, or advising without review where accuracy matters.
For law and accounting leaders, that means defining handoffs clearly. The AI can prepare the work, but a human should confirm the facts, check the judgment call, and decide whether the result is fit for client-facing use.
The hiring signal is the same signal for marketing
The hiring article and the LinkedIn update point to the same operating principle: AI use is becoming normal, but trust still depends on verification. Employers are wary when they cannot tell whether candidate materials reflect actual skill, and audiences feel the same way when they see low-quality automated content.
That makes evaluation a core management issue. Firms need simple checks for content quality, factual accuracy, and brand fit before AI-assisted work reaches clients, prospects, or the market.
- Use AI to support expert workflows, not to mass-produce generic content.
- Build review steps into every client-facing AI workflow.
- Treat authenticity and quality control as part of your firm's brand.
- Start with narrow use cases where the output can be evaluated easily.
Sources watched
- 87% of Employers Use AI to Hire - But 82% Are Wary of Candidates Doing the Same (CPA Practice Advisor AI)
- LinkedIn is Cracking Down on 'AI Slop' with New Reporting Tool (CPA Practice Advisor AI)
