The latest news across law, audit, and tax points to the same operating reality for professional-services firms: technology alone does not solve leadership, quality, or delivery problems. The firms that benefit most from AI will be the ones that pair clear judgment with workflows designed around real work.
The new AI playbook is about work design, not hype
A recent in-house legal framework from SSE's Emily Bull uses a simple test for each task: can it be eliminated, enabled for someone else, engineered into a better process, or does it truly require expertise? That is a useful lens for law and accounting firm leaders who want to move beyond generic chat tools and toward practical automation.
For firms, the first question is not whether AI can do everything. It is which work should be removed, reassigned, streamlined, or reserved for senior review. That mindset creates a better starting point for custom AI and agentic workflows than trying to automate everything at once.
Governance matters as much as the workflow itself
The appointment of Dave Sullivan to lead the Center for Audit Quality underscores how closely leadership, trust, and quality remain linked in professional services. In audit and assurance, any technology adoption has to support quality standards and confidence, not just speed.
That same principle applies in law and accounting firms. Custom AI systems need clear review points, defined use cases, and controls around sensitive work. Without governance, automation can create more risk than value.
Why custom AI beats generic tools for firms
The discussion around the Weil crisis shows that firm instability is driven by people, economics, and client confidence, not simply technology. AI did not cause that crisis, and it will not fix structural problems by itself either.
What AI can do well is reduce friction in repeatable work, support decision-making, and help teams respond faster when the process is designed correctly. For professional-services firms, that argues for focused use cases such as intake, matter triage, research support, document handling, and internal knowledge workflows rather than broad, unfocused experimentation.
Leadership lessons from professional-services firms
Leigh D'Andrea's role at Deloitte highlights another useful point: large firms still run on teamwork, coaching, and distributed leadership. AI adoption should fit that reality. The best automation programs help teams work more consistently, not less humanly.
For law and accounting leaders, that means building workflows that support managers, not replace them. The goal is to create systems that make good judgment easier to apply at scale.
- Start with a task-by-task review: eliminate, delegate, improve, or retain for expert judgment.
- Treat governance, review, and quality control as part of the workflow design, not afterthoughts.
- Prioritize narrow, high-volume use cases where custom AI can save time without eroding trust.
- Use leadership principles from professional services-teamwork, coaching, and accountability-to guide adoption.
Sources watched
- AI Didn't Cause the Weil Crisis (Artificial Lawyer)
- The 4 Es Inhouse AI Framework - Emily Bull (Artificial Lawyer)
