KPMG Analyst Event & “Velocity” Launch

KPMG was the fastest-growing of the “Big Four” firms last year, closing the gap on its three larger peers in the tax, audit, and advisory markets.

PAC recently spent time with the firm’s leadership and some of its leading clients at KPMG’s Lakehouse in Orlando to understand the drivers behind its business and how its major bet on AI is playing out.

Customer Stories

KPMG’s IT services capabilities are driven through its $16.3bn advisory division, which aims to combine deep industry domain capabilities with a growing technology services capability.

As we explored 18 months ago, KPMG has been aggressively ramping up its alliances with platform providers such as SAP, ServiceNow and Salesforce (building on more established partnerships with Oracle and Microsoft). And several of the clients shared how they had engaged with KPMG to help them join-the-dots between the functionality in these platforms and their critical business challenges.

For example, an international retail group selected KPMG to help it scale its e-commerce activities and to drive a better and more personalized customer experience. KPMG’s retail experts helped the business to harness the Salesforce platform in a way that mapped to a “north star” vision of how it wanted to function, rather than trying to reengineer the technology to fit its existing processes. This has enabled the company to build a 360-view of the customer across multiple channels and touchpoints, while significantly improving and streamlining processes such as returns and enhancing store profitability.

The depth of KPMG’s industry knowledge is showcased with its work with a major global pharmaceutical company in helping it build and scale its strategy in precision medicine. This is becoming the main battleground for the sector, as companies harness AI to predict more accurately which disease prevention and treatment strategies will work best for different groups of people. KPMG brought together a team of scientists and other experts from across the group to help it ensure that it successfully tackled international regulation, supply chain and taxation challenges, while supporting all the underlying data management and analytics programmes.

In the public healthcare space, KPMG has multiple engagements in the public healthcare sector, including a role in implementing a cutting-edge national data platform. The platform, based on Palantir, is designed to make it easier for frontline workers systems to access the information they need. KPMG and Palantir had previously delivered a pilot programme, which helped to optimize patient scheduling resulting in a 5% increase in theatre utilization, enabling thousands of additional treatments.

Outcomes & Optimization

This focus on delivering business outcomes will be crucial to KPMG’s future success, according to the group’s Global Head of Advisory, Carl Carande.

He states that the company is increasingly being compensated based on the value that it creates, rather than on the time-and-materials models that have long been the basis of the consulting market.

Carande highlighted several typical triggers for why business leaders work with KPMG, including improving performance, modernizing the technology landscape and enhancing stakeholder trust. PAC also heard from a major US manufacturing group, which had a broad-scope engagement with KPMG encompassing business and digital transformation, whose goal was to significantly accelerate the time it took to achieve value from its increasingly aggressive M&A strategy down from years to months.

One of the factors that we heard from multiple KPMG clients was that they found the vendor to be more successful than others in overcoming the organizational silos with which all big consulting and IT services vendors wrestle. One manufacturing client cited KPMG’s ability to pull together multi-disciplinary teams from advisory and tax with relevant industry domain experience, while a retail customer cited KPMG’s ability to provide a single partner with full accountability across the entire relationship as a vital part of their ongoing relationship.

KPMG is also benefitting from some wider structural changes that are playing out across the group. The group is on a journey to slim down from 150 different operating units down to between 30 to 40, which has already included the merger between the UK and Switzerland practices last year. the aim is to drive a greater level of portfolio and practice consistency to its international accounts, as well as accelerating its time-to-market with project delivery and new service offerings.

Velocity and AI

The whole event’s messaging was geared toward supporting the launch of KPMG Velocity. KPMG describes this new AI-enabled transformation platform as combining “KPMG Connected Enterprise, KPMG Powered Enterprise, KPMG Trusted Imperative, and KPMG Elevate with industry insights, AI, data, ESG, cyber, risk and regulatory considerations, transformation assets and more, in one place.”  

While this description is a bit of a mouthful, KPMG refreshingly shied away from aligning the platform with the overhyped concepts of Agentic AI or Services-as-software. Instead, it presented a string of case studies to convey a differentiation around holistic, namely multi-disciplinary transformation. Holistic means this journey is across silos and functions; therefore, the emphasis is holistic transformation rather than point solutions. In KPMG’s view, the key is algorithmic learning that enables clients to drive the cultural change necessary to successfully deliver transformation. Put another way, Velocity depicts the journey and the roadmap for clients to help them navigate the complexity of transformation (and of KPMG). Danielle Beringer, Principal, Data Strategy & Chief Technology Officer, Value, in the US, summarized what Velocity means to KPMG:” It is akin to muscle tissue that pulls through our capabilities.”

So, how should organizations think about this new platform? In essence, it is an interactive library to help design individual transformation journeys. Executives can select specific goals and motivations for those journeys and then connect them to existing KPMG offerings. Domain expertise is the secret sauce, as are the new AI capabilities we will discuss in a moment. Another way of looking at it is that these are curated transformation conversations across a set of personas. For KPMG, the key is to provide the relevant information, not just an input dump. What makes the platform stand out is that talent strategies are embedded because it is here where so many transformations fail.

The other focal point of the event was highlighting the progress in building out the firm’s AI portfolio. The cornerstone of this effort is the Workbench Program, which aims to standardize how AI solutions are being developed across all member firms across KPMG. All solutions design is focused on reusable code that capabilities can be delivered globally, even in markets with strong data regulation, such as Germany. KPMG acknowledged that initially, the costs for building solutions with AI went through the roof. As a response, KPMG installed guardrails centered on providing telemetry data following the identity of employees using AI tools and installing chargeback mechanisms to get a handle on costs. The building block of the Workbench include:

• aIQ Chat: Everyday AI UI/UX exposing agents, models, and RAG capabilities
• Agents: A common framework for the development, registry, and consumption of agents
• RAG: Portfolio of modular patterns for content ingestion and retrieval
• Core Platform: GenAI service infrastructure, model delivery, and tenant automation
• Cloud Vendors: The platforms and PaaS services that models and services are delivered
• Trust AI: Ethical, trusted, secure services and capabilities.

The Workbench Program was designed in collaboration with eight member firms and Microsoft. As its effectiveness has been demonstrated, KPMG is now in the process of certifying all of its member firms. The goal is to accelerate collaboration across the firm. The next step on this journey is to move to an agent factory model in low-cost locations, thus moving on from the earlier emphasis on prompt engineering. Ultimately, there was no escaping the hype around Agentic AI after all.