Posted January 30, 2025The Rise of Vertical AI in Accounting Marc Andrusko, Seema AmbleFollowing the publication of Death, Taxes, and AI, our look at how generative AI is permeating the accounting market, and our video discussion on the same topic, we heard from countless accounting professionals who are excited for what gen AI can unlock for their profession. From our conversations, we learned that while AI pilot programs are prevalent industrywide and firms are enthusiastic to try them, fully deployed vendor relationships are still relatively scarce. This is probably because AI models are not yet as proficient with numbers as they are with text, and because accountants (unsurprisingly) are fairly risk averse. As such, we wanted to offer a quick update on one big trend we’re observing within accounting firms, and the implications for builders looking to serve them.Nearly every accounting firm, large or small, to whom we spoke brought up one specific growth vector: Client Advisory Services, or CAS. CAS comprises a mix of outsourced CFO and controller services, making it a particularly strategic department for three reasons. CAS creates sticky, recurring relationships with clients that can serve as the basis for cross-selling engagements into other parts of the firm (namely tax and audit).
CAS revenue growth is outpacing broader accounting-firm revenue growth. Firms with a CAS practice are reporting 30% median revenue growth year over year, while the industry at large reports ~9% annual growth in net-client fees.
Qualitatively, CAS broadens the surface area for advisory revenue, which can often be more predictable and less seasonal than traditional accounting and tax engagements.
But with scaled CAS, comes great labor needs! Many of the activities that constitute outsourced controller services (e.g., helping with month-end closes, transaction reconciliation, expense management, etc.) require a person to repetitively perform rote tasks; we’ve previously referred to these “jobs to be done” as data collection and ingestion. Additionally, this manual extraction of data (from invoices, contracts, emails, general ledgers, and the like) is work that’s usually completed by a junior CPA or by an offshore laborer. The promise made by AI for accounting is to cut time spent on these activities down from hours to minutes, delivering immediate ROI in the form of freed-up labor hours. While this sounds ideal, it’s much harder to pull off than one might think, even with the powerful new technologies that underpin our current wave of AI-native accounting applications. For starters, accounting is a field in which accuracy is of paramount importance. For software to actually free up firms to either repurpose the skilled labor currently performing this work or end relationships with third-party BPOs, it has to actually work. Not only that, it needs to work “horizontally” across industries, many of which are riddled with unique data sources (indust
