Refactoring the Office of the CFO
PriceWaterhouseCoopers and Anthropic have announced a partnership which effectively significantly disrupts how the office of the CFO will work going forward, Anthropic and PwC Expand Alliance, Driving Impact Across Client Work and the Firm.
The partnership accelerates a shift from “accountants doing tasks” to “accountants supervising AI agents that perform tasks inside governed workflows.” This is already happening inside PWC’s own finance operations and in client deployments.
Let the refactoring begin!
Per the article, PwC and Claude are selling governance, not just agent speed, the value of the PWC and Claude combination is auditability, risk controls, and regulated workflow design; and not simply faster agent output.
According to Digital Applied; 3 of the Big 4 now run on Anthropic' s Claude: PWC, Deloitte, and KPMG. EY is using Microsoft.
Anthropic’s foundation models and agentic tools are fully proprietary. These include Claude, Claude Code, and Claude Cowork.
PWC’s deployment is proprietary at the model and workflow layer, but standards-based at the integration and governance layer it appears. PWC is building Claude-native workflows that are not open standards, they are PWC’s internal IP and client-facing delivery assets. Model Context Protocol (MCP) which is a standard is being used for integration between LLM applications and external data sources and tools. This approach lets PWC build defensible IP while still satisfying audit, compliance, and regulated‑industry requirements.
MCP, which was initially created by Anthropic was open sourced in 2024. MCP is often described as the "USB-C of the AI world", providing a universal, standardized connection between AI systems and external tools, making AI applications more capable, interoperable, and scalable.
It seems to me that the power of MCP as a USB-C connector is over stated. I say this because, first you have the problem of the document (as contrast to graph first knowledge) that I explain in Mind the Gap. Second, you still have the problem of semantic fragmentation that I go over in Fragmentation and Defensible Compliance. Third, you still have the whole problem related to Meaning. If you don't understand this, please read Digital Information Organism and Professional Oriented Knowledge Frameworks. And then, of course, you have the problem of "messy data" which is clearly explained by The AI Ladder. And finally, you have the problem of the electronic spreadsheet where PWC admits the best they have ever been able to do is get up to somewhere between 74% and 87% accuracy; however, that was with OpenAI. The work around is humans fixing problems. BOTTOM LINE: You would be hard pressed to call this an industrial process.
Some things worth noting about PWC's and Anthropic's announcement. Per this LinkedIn post and per this analysis, the business model created is effectively a "land-and-expand" consulting play in the banking, insurance, and healthcare sectors. The AI product is the "door" and the transformation engagement of the business.
PWC has set up a center of excellence and will train and certify 30,000 US based consultants initially on Claude and eventually on Claude Code and Claude Cowork.
Deloitte, KPMG, and EY will very likely take similar approaches. This article, PwC Claude CFO vs Deloitte AI vs McKinsey QuantumBlack, compares and contrasts the offerings from PWC, Deloitte, and McKinsey.
What I don't understand is the true capabilities being offered here. As I have pointed out in this blog post, Human Task Performance, there are different "flavors" of artificial intelligence. Not sure if what is being offered is the full spectrum of flavors or only one flavor.
Regardless, changing the paradigm of how the office of the CFO operates will take years. What PWC, Deloitte, KPMG, EY, and McKinsey is still "pre-science"; the "new normal" has not quite emerged but it is beginning to take shape. Also, while the Big 4 are focused on the large enterprise, what is going on is going to affect every enterprise; large, medium, small; public; private; not-for-profit; government.
The full transformation is not just "building out the enterprise knowledge graph" so that artificial intelligence can be leveraged. I predict that enterprises will shift from a document-based architecture to a model-driven architecture. This will take time, but it is inevitable because you need the model-driven architecture to build industrial processes. I predict that accounting will be refactored to begin at the beginning with the business event as contrast to starting later in the chain.
The office of the CFO is only the beginning of the refactoring of the enterprise enable to take full advantage of the opportunity artificial intelligence brings to the table.
I cannot tell for sure, but it seems like what PWC and Anthropic have is perhaps not full neuro‑symbolic artificial intelligence with human teaming. But it does seem to be a hybrid system where you have neural models constructed by the machine, symbolic workflows constructed by humans, governed connectors to information sources, enterprise schemas defined by MCP, and audit trails. All these seem to work together in a way that is perhaps functionally neuro‑symbolic, even if not formally integrated. It is, perhaps, a practical version of neuro‑symbolic artificial intelligence.
BOTTOM LINE: Buyer beware. Artificial intelligence absolutely is a real thing and it will absolutely enable a refactoring of the office of the CFO and the entire enterprise. Right now, I don't know exactly were we are on the Gartner Hype Cycle, but I would speculate it would be at the "Peak of Inflated Expectations". We still have the "Trough of Disillusionment" to go. As The AI Ladder points out, 81% of business leaders don't understand the data and infrastructure required for AI. Watch out for the snake oil salesmen trying to separate you from your hard earned money. The "Plateau of Productivity" will be reached...but we are not there currently.
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