Forvis Mazars has launched Chinese and Japanese Desks to support U.S. multinational enterprises with business interests in China and Japan. At the same time, accounting technology providers are pushing AI-powered advisory and enterprise tools, while legal AI educators are asking how lawyers should be trained to work with AI in everyday practice. For firm leaders, the common thread is clear: the next productivity gain is likely to come from coordinated workflows that connect people, client data, compliance needs, and judgment.
International desks show why coordination is the real service layer
Forvis Mazars says its new Chinese and Japanese Desks provide a dedicated point of contact to improve coordination between the firm's U.S. teams and team members located in those countries. The desks include audit, tax, and advisory professionals and are intended to support multinational clients with local laws, regulations, strategic advice, and operational advice.
That structure matters for AI strategy. Cross-border client service is not a single chatbot interaction. It involves routing questions, tracking jurisdiction-specific issues, coordinating internal experts, and making sure the client receives culturally aware, consistent guidance. A custom AI workflow for a firm like this would need to support the desk model, not replace it.
AI advisory tools are moving closer to the client-data layer
Wolters Kluwer said CCH Axcess Advisor is now commercially available to U.S. firms moving from compliance-centric work to an advisory-led service model. The company describes it as an AI-powered advisory solution that helps firms identify, prioritize, and deliver advisory services by turning existing client data into growth opportunities within current workflows.
That is the right direction for many accounting firms: AI becomes more useful when it is connected to the data and decisions already inside the practice. For a custom build, the operator question is not simply, "Can AI summarize this?" It is, "Can the workflow surface the right client, the right advisory opportunity, the right next step, and the right reviewer?"
Enterprise automation raises expectations for multi-entity clients
Intuit also announced enhancements to Intuit Enterprise Suite, described as an AI-powered business platform that brings together financial, payroll, human resources, marketing, and cash flow tools. The company highlighted real-time insights, automation for complex financial management processes, integration of human capital management operations and money transactions, new capabilities for multi-entity businesses, dimensional reporting, and construction-specific capabilities focused on cash flow.
Professional-services firms advising mid-market or multi-entity clients should expect those clients to ask for faster, more connected answers. If a client's operating platform is becoming more automated, the firm's advisory process cannot remain a slow chain of inboxes, spreadsheets, and manual status checks.
Legal AI training is becoming an operating issue, not a side topic
Artificial Lawyer reported that Litera and Artificial Lawyer are hosting a webinar on education and training in the age of legal AI, with speakers from Stanford Law School, Linklaters, The University of Law, and Litera. The webinar overview frames the issue plainly: law students may be experimenting with legal technology and generative AI, but experimentation in school and confidence on day one at a firm are different things.
The same gap exists inside firms. Buying an AI tool does not automatically create a reliable workflow. Lawyers, accountants, business development teams, and clients need shared expectations about what AI is used for, who reviews the output, and where the workflow hands work back to a human professional.
Compliance scrutiny is a reminder to build review into the workflow
The SEC-related Musk settlement story is not an AI story, but it is a useful reminder for firms building AI-assisted workflows. A federal judge said she could not "rubber stamp" a proposed $1.5 million settlement and ordered attorneys to answer questions about how the deal was reached, including why it involved a trust tied to Musk instead of Musk himself.
For professional-services firms, the lesson is operational: high-stakes matters need documented reasoning, review points, and clear ownership. AI and automation can help organize work, but firm leaders should design workflows so that sensitive judgments are visible, reviewable, and assigned to accountable professionals.
- Design AI around the firm's service model: desks, practice groups, reviewers, and client teams should be reflected in the workflow.
- Use client data to trigger advisory opportunities, but keep prioritization and delivery tied to professional judgment.
- Training matters as much as tooling; teams need to know when to rely on AI, when to verify, and when to escalate.
- For regulated or high-stakes work, build review, documentation, and ownership into the automation from the start.
Sources watched
- Forvis Mazars Expands International Desks to Include China and Japan (CPA Practice Advisor AI)
- Judge Says Cannot 'Rubber Stamp' $1.5 Million Musk-SEC Deal (CPA Practice Advisor AI)
- Litera Webinar: Education + Training in the Age of Legal AI (Artificial Lawyer)
- Wolters Kluwer Says CCH Axcess Advisor is Now Readily Available to Firms (CPA Practice Advisor AI)
- Intuit Announces Several Enhancements to Intuit Enterprise Suite (CPA Practice Advisor AI)
