Global professional services leader KPMG LLP has entered a strategic relationship with Business AI provider Uniphore to jointly develop AI agents powered by industry‑specific small language models (SLMs) that will advance production‑grade AI deployment across regulated sectors such as banking, insurance, energy and healthcare. The collaboration aims to move beyond isolated AI experimentation and embed governed, scalable AI capabilities directly into enterprise workflows — a development with far‑reaching implications for the revenue industry and business operations more broadly.
The initiative will leverage Uniphore’s Business AI Cloud as the foundation for agentic AI and fine‑tuned SLMs that support both internal processes and client‑facing services. These models, designed for highly regulated environments, will operate alongside KPMG’s existing enterprise systems and data platforms, ensuring compliance with governance standards while enabling AI to execute complex business tasks effectively.
According to Prasad Jayaraman, Advisory Principal at KPMG, the collaboration reflects a shared commitment to turning theoretical AI pilots into real operational value by embedding the technology into the way work actually gets done — in a manner that is governed, secure and aligned with business needs.
AI Agents That Work Within Complex Enterprise Environments
One of the primary goals of this partnership is to train KPMG’s consulting workforce not only to design and govern AI agents but also to deploy them within mission‑critical workflows. This model blends human judgment with autonomous AI execution, enabling teams to drive outcomes more consistently and at scale. Uniphore’s Business AI Cloud supports the transformation of institutional knowledge — including regulatory frameworks, organizational playbooks and documented processes — into reusable AI models that can automate complex tasks across industries.
Some of its main initial applications are AI-infused contracting and procurement, where AI bots are capable of automatically identifying and classifying high-value contracts, and then deriving obligations and comparing them with approved standards, while also pointing out possible risks and submitting exceptions for processing. By incorporating these AI bots right into business processes, companies are able to decrease revenue leakage and contracting cycles.
Impact on the Revenue Industry
The KPMG–Uniphore strategic relationship signals a paradigm shift in how revenue‑related functions can evolve with AI. Traditionally, many revenue operations, including billing, financial reporting, compliance, and contract management, have relied on time-consuming, highly document-intensive, error-prone processes. Embedding AI agents capable of understanding domain-specific data and executing tasks autonomously transforms these workflows in a number of ways:
Efficiency of Operations: The AI agents can perform routine tasks related to revenue recognition, the quote-to-cash process, contract compliances, among other functions, which were previously the duties of human resources.
Minimizing Revenue Leakage: Automation enabled by AI will help companies capture revenues that would otherwise be lost as a result of a dispute or failure. This is achieved though improved contract reviews and billings.
Improved Compliance and Risk Mitigation: SLM-driven agents will be capable of incorporating knowledge of regulations and governance to lower risk and, as such, support better reporting, which translates to revenue integrity in their respective industries.
This trend toward agentic AI in revenue workflows aligns with industry‑wide moves to leverage AI not just for insight, but for execution — where systems act and adapt as part of daily operations rather than simply analyze data in isolation.
Broader Business Effects
In regulated and complex markets in which businesses operate, the following collaboration between KPMG and Uniphore is of greater strategic significance:
Scalability without Fragmentation: Because the AI agents are created to run on the reliable enterprise data platforms such as Databricks and Snowflake, it does not create the need for the construction of shadow systems and the replication of the data.
Improved Decision-Making: Since AI is ready to undertake tasks ranging from purchasing to talent optimization, executives are now better informed and better positioned to make decisions.
Competitive Advantage: Those businesses that are able to build AI into key processes are better equipped to deal effectively and efficiently with changes in the marketplace, regulations, and demands.
As organizations increasingly prioritize intelligent automation within revenue processes — from contract lifecycle management to finance transformation — this collaboration represents a key milestone in bringing scalable, enterprise‑grade AI into mainstream revenue operations. With an emphasis on secure data integration, real‑world workflows and tangible outcomes, KPMG and Uniphore are helping shape the future of how businesses generate, protect and accelerate revenue in an AI‑infused era.
