KPMG, the professional services network with US$39.8 billion in annual global revenue
Artificial intelligence is changing what companies expect from professional services.
For decades, organizations hired firms such as KPMG to audit financial statements, navigate tax regulations, manage risk, implement technology and advise executives on major strategic decisions. Now, many of those same activities are being reshaped by AI.
KPMG is responding with something broader than simply adding AI tools to traditional consulting.
The company is redesigning how professional services are delivered.
Its strategy combines artificial intelligence, managed services, cloud technology, cybersecurity, data and human expertise into a model designed to help companies move from experimenting with AI to operating it at scale.
That transformation is turning KPMG into something increasingly different from the accounting firm of the past — although the spreadsheets, presumably, remain under supervision.
A Global Professional Services Network
KPMG is one of the world’s largest professional services organizations, operating through a network of independent member firms.
Its global organization provides three principal categories of services: Audit, Tax & Legal, and Advisory.
The network operates across 142 countries and territories, with more than 276,000 partners and employees. In FY2025, KPMG firms generated US$39.8 billion in globally aggregated revenue, representing 5.1% growth in local currency and 5.4% in U.S. dollars. (KPMG)
The three businesses contributed approximately:
→ US$14.1 billion from Audit
→ US$16.4 billion from Advisory
→ US$9.3 billion from Tax & Legal
All three grew during FY2025, with Tax & Legal increasing 7.5%, Audit 6.0% and Advisory 2.9%. (KPMG)
KPMG’s global chairman and CEO is Bill Thomas. (KPMG)
These figures matter because they reveal the scale of the organization KPMG is now attempting to transform.
This is not a technology startup adding professional services.
It is a professional services network attempting to become increasingly technology-driven — without losing the institutional trust that made its business possible in the first place.
The Old Professional Services Model Is Changing
The traditional professional services model is fundamentally based on expertise.
Companies hire specialists because they need knowledge they do not possess internally.
Auditors examine financial information. Tax specialists interpret increasingly complex rules. Consultants analyze business problems. Technology teams implement systems. Advisors help executives navigate uncertainty.
AI changes the economics of each activity.
A system can analyze thousands of documents faster than a human team. It can identify patterns across enormous datasets, generate first drafts, monitor transactions and automate repetitive research.
That does not eliminate the need for professionals.
Instead, it changes where their time and expertise create the most value.
KPMG’s strategy is increasingly based on this transition.
The company wants AI to automate portions of professional work while allowing its people to concentrate on judgment, interpretation, relationships and complex decisions.
Its own 2026 Impact Plan explicitly describes a human-centric approach to AI, with human judgment, expertise and ethical decision-making remaining central to how KPMG deploys the technology. (KPMG)
That philosophy is particularly important in professional services because trust is part of the product. AI may draft the memo, but someone still has to be willing to sign it.
KPMG Is Becoming Its Own Test Case
One of the most interesting parts of KPMG’s AI strategy is that the company is treating itself as “client zero.”
Instead of only advising customers about AI transformation, KPMG is applying those principles internally and using the experience to refine the services it provides to clients.
The company describes this approach as walking the talk in an AI-powered world: redesigning its workforce and operating model around AI while maintaining human oversight. (KPMG)
This creates a feedback loop.
KPMG experiments internally.
It learns which technologies work.
It identifies governance and implementation problems.
It develops methodologies.
Then it takes those lessons into client engagements.
The firm’s own transformation therefore becomes part of its intellectual capital. In other words, KPMG is not merely selling the map; it is testing the route while the road is still being built.
AI Is Moving Into Audit
Audit is one of the areas where the impact of AI could be particularly significant.
KPMG’s KPMG Clara platform is designed to use data and AI to make auditing more efficient and help professionals focus on areas where risk is concentrated.
The company’s position is not that AI replaces auditors.
Instead, AI can process more information, identify anomalies and support the auditor’s analysis, while professional judgment remains central to the final work. (KPMG)
This changes the nature of the audit workflow.
Historically, large amounts of professional time could be spent gathering information, reviewing transactions and performing repetitive procedures.
AI can increasingly perform portions of that work continuously and at greater scale.
The professional then moves further toward interpretation and judgment.
That could eventually redefine what clients expect from an audit firm — and make “sampling” a much less comforting word in certain boardrooms.
Tax Is Becoming Software-Driven
The same transformation is taking place in tax.
Tax departments operate in environments where rules change frequently, data is distributed across systems and regulatory requirements can be extremely complex.
KPMG is building AI capabilities designed to help tax professionals analyze information, automate processes and manage increasingly sophisticated compliance requirements.
Its KPMG Digital Gateway, for example, is positioned as a platform for tax functions seeking to develop and deploy responsible generative AI programs. (KPMG)
The strategic shift is important.
KPMG is moving from selling professional hours toward combining professional expertise with technology platforms.
The more work that can be embedded into software and managed services, the more scalable the relationship becomes.
The objective is not to make tax simple — that may be beyond the reach of civilization — but to make it more structured, transparent and manageable.
The Managed Services Opportunity
Perhaps the clearest expression of KPMG’s transformation is its expansion into managed services.
The traditional consulting model often ends when a project ends.
Managed services create a different relationship.
The professional services firm remains involved in operating part of the client’s process, increasingly supported by cloud platforms, automation and AI.
KPMG’s 2026 Managed Services Outlook found that 87% of organizations had already integrated managed services into their digital transformation strategies, while more than 90% of executives viewed managed services as essential to delivering agentic AI. The survey covered 1,224 senior leaders across major global markets. (KPMG)
This changes the economic relationship between KPMG and its clients.
Instead of simply advising a company about how to use AI, KPMG can increasingly help operate the systems through which AI is deployed.
That creates recurring relationships around technology, data, governance and operations.
It also moves the firm closer to the client’s day-to-day infrastructure — where the budgets are recurring, the expectations are high and the coffee is rarely optional.
AI Is Becoming An Operating Model
KPMG’s own research suggests that companies are moving beyond experimentation.
Its Q2 2026 Global AI Pulse found that 79% of business leaders identified AI as a key investment area, up from 74% in the previous quarter. Average reported AI spending was approximately US$188 million among the organizations surveyed. (KPMG)
But spending is not the same as value creation.
One of the emerging problems is the economics of running AI at scale.
KPMG’s research found that only 26% of organizations had real-time visibility into the cost of operating AI at scale. Meanwhile, agent deployment remained above 50%, with companies increasingly experimenting with multiple agents working across enterprise workflows. (KPMG)
This creates an entirely new consulting opportunity.
Companies do not only need help building AI.
They need help understanding what AI costs, where it creates value, how it should be governed and how humans should interact with autonomous systems.
That is precisely the territory KPMG is moving toward.
The uncomfortable truth is that many companies now know how much they are spending on AI, but not necessarily what the AI is doing with the money.
Trust Is Becoming A Technology Problem
AI creates another problem for professional services firms: trust.
A company can deploy an AI system in days.
That does not mean it should.
Financial information, customer data, intellectual property and sensitive corporate decisions can pass through AI systems. Errors can create regulatory, financial and reputational consequences.
KPMG has therefore made Trusted AI a central component of its strategy.
The firm’s framework is designed around responsible and ethical AI development and deployment, with controls covering areas such as governance, risk, security and accountability. KPMG appointed a global Trusted AI Leader during FY2025 to help embed these principles across its AI capabilities. (KPMG)
This is becoming commercially important.
KPMG’s June 2026 research found that nearly three-quarters of executives identified risk, security and privacy as major concerns around AI, yet only 24% said those considerations were embedded into strategy and technology effectively. (KPMG)
The gap is substantial.
Companies want AI.
They also need someone to help them control it.
Because “the model made a mistake” is unlikely to be accepted as a complete risk-management strategy.
The Agentic AI Shift
Generative AI was initially centered around assistants.
The next stage is increasingly about agents.
Instead of simply answering a question, an AI agent can potentially interpret a task, access systems, make decisions within predefined boundaries and coordinate multiple steps.
That creates a much larger transformation in enterprise software.
An organization could eventually have AI agents handling portions of finance, procurement, customer operations, tax compliance, cybersecurity and other workflows.
But autonomous systems also introduce new risks.
Who approves the decisions?
Who monitors the agents?
What happens when two agents produce conflicting actions?
How much does each workflow cost?
What data can the system access?
KPMG is positioning itself directly inside these questions.
Its managed-services research found that more than 90% of executives see managed services as essential to delivering agentic AI. (KPMG)
The company is therefore attempting to become part of the infrastructure required to operate an AI-enabled enterprise.
The opportunity is significant, but so is the governance challenge: giving software more autonomy does not eliminate accountability. It simply makes the org chart more interesting.
KPMG Is Investing Billions In The Transformation
The transformation requires capital.
KPMG has committed to a multi-year global investment program involving more than US$4 billion over four years across innovative services, technologies and acquisitions.
The investment is focused on areas including artificial intelligence, automation, cybersecurity and intelligent audit and tax platforms. (KPMG)
This is important because professional services organizations historically depended heavily on human capital.
KPMG is increasingly investing in technological capital as well.
The objective is not necessarily to replace its workforce.
It is to increase the amount of value that each professional can generate by giving them better technology.
That distinction will shape the firm’s economics over the next decade.
The Economics Of Human Expertise Are Changing
Professional services have traditionally scaled by adding people.
More clients required more consultants, auditors, tax specialists and lawyers.
AI introduces another possibility.
If software can perform part of the work, a professional can potentially serve more clients without a proportional increase in headcount.
That could improve productivity.
It could also change the composition of the workforce.
KPMG’s own research estimates that generative AI could create an opportunity equivalent to 4–18% of EBITDA across sectors, although capturing that value depends heavily on organizational change, workflow redesign and adoption rather than simply deploying the technology. (KPMG)
For KPMG, this creates both an opportunity and a challenge.
The company can sell AI transformation to clients.
But it must also prove that AI can transform KPMG itself.
That means demonstrating productivity gains without reducing professional judgment to a checkbox in a workflow.
The Professional Services Firm Of The AI Era
KPMG’s long-term transformation is therefore larger than automation.
It is a change in the nature of the firm.
The traditional KPMG was built around professionals selling expertise.
The emerging KPMG is increasingly built around professionals + software + data + AI + managed services.
That combination could allow the firm to participate in more parts of the enterprise value chain.
It can advise a company on AI strategy.
Help design the architecture.
Implement the technology.
Audit the resulting systems.
Manage parts of the operation.
And provide ongoing services through AI-enabled platforms.
The relationship becomes more continuous.
The firm is moving from project-based expertise toward an integrated model in which advice, technology and operations reinforce one another.
The Risk Is That AI Changes KPMG’s Own Business
The transformation also creates a paradox.
KPMG is helping clients automate professional work while much of its own economic model has historically depended on professionals performing that work.
If AI dramatically reduces the amount of human labor required for certain services, the industry could face significant pressure on traditional billing models.
The answer cannot simply be to sell more hours.
The value proposition must move toward outcomes.
That means KPMG increasingly needs to demonstrate that it can help clients achieve measurable improvements in productivity, risk management, compliance, technology performance and business results.
AI makes that shift more urgent.
The firms that adapt fastest may be those that stop treating AI as a feature and start treating it as a redesign of the business model.
Why KPMG Matters
KPMG is not building a foundation model.
It is not competing with the companies developing the largest AI systems.
Its opportunity lies somewhere else.
The enterprise AI economy needs organizations capable of connecting technology with business processes, governance, regulation, cybersecurity and human decision-making.
That is the environment KPMG has spent decades operating in.
Its advantage is therefore not the AI model itself.
It is the combination of institutional trust, professional expertise, global relationships, regulatory knowledge and increasingly sophisticated technology infrastructure.
The company’s US$39.8 billion global revenue base gives it enormous scale from which to make that transition. (KPMG)
The question is what that organization looks like after the transformation is complete.
If the traditional professional services firm sold expertise by the hour, the emerging model could increasingly sell intelligence embedded in workflows.
Audit becomes more continuous.
Tax becomes more automated.
Consulting becomes more data-driven.
Managed services become more autonomous.
And AI becomes part of the operating infrastructure rather than an isolated technology project.
KPMG is betting that the professional services firm of the future will not simply advise companies about artificial intelligence.
It will help build, govern and operate the systems through which those companies use it.
The winning formula may be less about replacing professionals than about giving them better leverage — and ensuring that the machines know when to stop talking and let an expert take over.
Market Snapshot
Company: KPMG International
Founded: 1987
Headquarters: Amstelveen, Netherlands
Industry: Professional Services
Global Revenue FY2025: US$39.8 billion
Global Employees: 276,030
Countries & Territories: 142
FY2025 Audit Revenue: US$14.1 billion
FY2025 Advisory Revenue: US$16.4 billion
FY2025 Tax & Legal Revenue: US$9.3 billion
Global Chairman & CEO: Bill Thomas
Global Investment Program: US$4+ billion over four years
gence is changing what companies expect from professional services.
For decades, organizations hired firms such as KPMG to audit financial statements, navigate tax regulations, manage risk, implement technology and advise executives on major strategic decisions. Now, many of those same activities are being reshaped by AI.
KPMG is responding with something broader than simply adding AI tools to traditional consulting.
The company is redesigning how professional services are delivered.
Its strategy combines artificial intelligence, managed services, cloud technology, cybersecurity, data and human expertise into a model designed to help companies move from experimenting with AI to operating it at scale.
That transformation is turning KPMG into something increasingly different from the accounting firm of the past — although the spreadsheets, presumably, remain under supervision.
A Global Professional Services Network
KPMG is one of the world’s largest professional services organizations, operating through a network of independent member firms.
Its global organization provides three principal categories of services: Audit, Tax & Legal, and Advisory.
The network operates across 142 countries and territories, with more than 276,000 partners and employees. In FY2025, KPMG firms generated US$39.8 billion in globally aggregated revenue, representing 5.1% growth in local currency and 5.4% in U.S. dollars. (KPMG)
The three businesses contributed approximately:
→ US$14.1 billion from Audit
→ US$16.4 billion from Advisory
→ US$9.3 billion from Tax & Legal
All three grew during FY2025, with Tax & Legal increasing 7.5%, Audit 6.0% and Advisory 2.9%. (KPMG)
KPMG’s global chairman and CEO is Bill Thomas. (KPMG)
These figures matter because they reveal the scale of the organization KPMG is now attempting to transform.
This is not a technology startup adding professional services.
It is a professional services network attempting to become increasingly technology-driven — without losing the institutional trust that made its business possible in the first place.
The Old Professional Services Model Is Changing
The traditional professional services model is fundamentally based on expertise.
Companies hire specialists because they need knowledge they do not possess internally.
Auditors examine financial information. Tax specialists interpret increasingly complex rules. Consultants analyze business problems. Technology teams implement systems. Advisors help executives navigate uncertainty.
AI changes the economics of each activity.
A system can analyze thousands of documents faster than a human team. It can identify patterns across enormous datasets, generate first drafts, monitor transactions and automate repetitive research.
That does not eliminate the need for professionals.
Instead, it changes where their time and expertise create the most value.
KPMG’s strategy is increasingly based on this transition.
The company wants AI to automate portions of professional work while allowing its people to concentrate on judgment, interpretation, relationships and complex decisions.
Its own 2026 Impact Plan explicitly describes a human-centric approach to AI, with human judgment, expertise and ethical decision-making remaining central to how KPMG deploys the technology. (KPMG)
That philosophy is particularly important in professional services because trust is part of the product. AI may draft the memo, but someone still has to be willing to sign it.
KPMG Is Becoming Its Own Test Case
One of the most interesting parts of KPMG’s AI strategy is that the company is treating itself as “client zero.”
Instead of only advising customers about AI transformation, KPMG is applying those principles internally and using the experience to refine the services it provides to clients.
The company describes this approach as walking the talk in an AI-powered world: redesigning its workforce and operating model around AI while maintaining human oversight. (KPMG)
This creates a feedback loop.
KPMG experiments internally.
It learns which technologies work.
It identifies governance and implementation problems.
It develops methodologies.
Then it takes those lessons into client engagements.
The firm’s own transformation therefore becomes part of its intellectual capital. In other words, KPMG is not merely selling the map; it is testing the route while the road is still being built.
AI Is Moving Into Audit
Audit is one of the areas where the impact of AI could be particularly significant.
KPMG’s KPMG Clara platform is designed to use data and AI to make auditing more efficient and help professionals focus on areas where risk is concentrated.
The company’s position is not that AI replaces auditors.
Instead, AI can process more information, identify anomalies and support the auditor’s analysis, while professional judgment remains central to the final work. (KPMG)
This changes the nature of the audit workflow.
Historically, large amounts of professional time could be spent gathering information, reviewing transactions and performing repetitive procedures.
AI can increasingly perform portions of that work continuously and at greater scale.
The professional then moves further toward interpretation and judgment.
That could eventually redefine what clients expect from an audit firm — and make “sampling” a much less comforting word in certain boardrooms.
Tax Is Becoming Software-Driven
The same transformation is taking place in tax.
Tax departments operate in environments where rules change frequently, data is distributed across systems and regulatory requirements can be extremely complex.
KPMG is building AI capabilities designed to help tax professionals analyze information, automate processes and manage increasingly sophisticated compliance requirements.
Its KPMG Digital Gateway, for example, is positioned as a platform for tax functions seeking to develop and deploy responsible generative AI programs. (KPMG)
The strategic shift is important.
KPMG is moving from selling professional hours toward combining professional expertise with technology platforms.
The more work that can be embedded into software and managed services, the more scalable the relationship becomes.
The objective is not to make tax simple — that may be beyond the reach of civilization — but to make it more structured, transparent and manageable.
The Managed Services Opportunity
Perhaps the clearest expression of KPMG’s transformation is its expansion into managed services.
The traditional consulting model often ends when a project ends.
Managed services create a different relationship.
The professional services firm remains involved in operating part of the client’s process, increasingly supported by cloud platforms, automation and AI.
KPMG’s 2026 Managed Services Outlook found that 87% of organizations had already integrated managed services into their digital transformation strategies, while more than 90% of executives viewed managed services as essential to delivering agentic AI. The survey covered 1,224 senior leaders across major global markets. (KPMG)
This changes the economic relationship between KPMG and its clients.
Instead of simply advising a company about how to use AI, KPMG can increasingly help operate the systems through which AI is deployed.
That creates recurring relationships around technology, data, governance and operations.
It also moves the firm closer to the client’s day-to-day infrastructure — where the budgets are recurring, the expectations are high and the coffee is rarely optional.
AI Is Becoming An Operating Model
KPMG’s own research suggests that companies are moving beyond experimentation.
Its Q2 2026 Global AI Pulse found that 79% of business leaders identified AI as a key investment area, up from 74% in the previous quarter. Average reported AI spending was approximately US$188 million among the organizations surveyed. (KPMG)
But spending is not the same as value creation.
One of the emerging problems is the economics of running AI at scale.
KPMG’s research found that only 26% of organizations had real-time visibility into the cost of operating AI at scale. Meanwhile, agent deployment remained above 50%, with companies increasingly experimenting with multiple agents working across enterprise workflows. (KPMG)
This creates an entirely new consulting opportunity.
Companies do not only need help building AI.
They need help understanding what AI costs, where it creates value, how it should be governed and how humans should interact with autonomous systems.
That is precisely the territory KPMG is moving toward.
The uncomfortable truth is that many companies now know how much they are spending on AI, but not necessarily what the AI is doing with the money.
Trust Is Becoming A Technology Problem
AI creates another problem for professional services firms: trust.
A company can deploy an AI system in days.
That does not mean it should.
Financial information, customer data, intellectual property and sensitive corporate decisions can pass through AI systems. Errors can create regulatory, financial and reputational consequences.
KPMG has therefore made Trusted AI a central component of its strategy.
The firm’s framework is designed around responsible and ethical AI development and deployment, with controls covering areas such as governance, risk, security and accountability. KPMG appointed a global Trusted AI Leader during FY2025 to help embed these principles across its AI capabilities. (KPMG)
This is becoming commercially important.
KPMG’s June 2026 research found that nearly three-quarters of executives identified risk, security and privacy as major concerns around AI, yet only 24% said those considerations were embedded into strategy and technology effectively. (KPMG)
The gap is substantial.
Companies want AI.
They also need someone to help them control it.
Because “the model made a mistake” is unlikely to be accepted as a complete risk-management strategy.
The Agentic AI Shift
Generative AI was initially centered around assistants.
The next stage is increasingly about agents.
Instead of simply answering a question, an AI agent can potentially interpret a task, access systems, make decisions within predefined boundaries and coordinate multiple steps.
That creates a much larger transformation in enterprise software.
An organization could eventually have AI agents handling portions of finance, procurement, customer operations, tax compliance, cybersecurity and other workflows.
But autonomous systems also introduce new risks.
Who approves the decisions?
Who monitors the agents?
What happens when two agents produce conflicting actions?
How much does each workflow cost?
What data can the system access?
KPMG is positioning itself directly inside these questions.
Its managed-services research found that more than 90% of executives see managed services as essential to delivering agentic AI. (KPMG)
The company is therefore attempting to become part of the infrastructure required to operate an AI-enabled enterprise.
The opportunity is significant, but so is the governance challenge: giving software more autonomy does not eliminate accountability. It simply makes the org chart more interesting.
KPMG Is Investing Billions In The Transformation
The transformation requires capital.
KPMG has committed to a multi-year global investment program involving more than US$4 billion over four years across innovative services, technologies and acquisitions.
The investment is focused on areas including artificial intelligence, automation, cybersecurity and intelligent audit and tax platforms. (KPMG)
This is important because professional services organizations historically depended heavily on human capital.
KPMG is increasingly investing in technological capital as well.
The objective is not necessarily to replace its workforce.
It is to increase the amount of value that each professional can generate by giving them better technology.
That distinction will shape the firm’s economics over the next decade.
The Economics Of Human Expertise Are Changing
Professional services have traditionally scaled by adding people.
More clients required more consultants, auditors, tax specialists and lawyers.
AI introduces another possibility.
If software can perform part of the work, a professional can potentially serve more clients without a proportional increase in headcount.
That could improve productivity.
It could also change the composition of the workforce.
KPMG’s own research estimates that generative AI could create an opportunity equivalent to 4–18% of EBITDA across sectors, although capturing that value depends heavily on organizational change, workflow redesign and adoption rather than simply deploying the technology. (KPMG)
For KPMG, this creates both an opportunity and a challenge.
The company can sell AI transformation to clients.
But it must also prove that AI can transform KPMG itself.
That means demonstrating productivity gains without reducing professional judgment to a checkbox in a workflow.
The Professional Services Firm Of The AI Era
KPMG’s long-term transformation is therefore larger than automation.
It is a change in the nature of the firm.
The traditional KPMG was built around professionals selling expertise.
The emerging KPMG is increasingly built around professionals + software + data + AI + managed services.
That combination could allow the firm to participate in more parts of the enterprise value chain.
It can advise a company on AI strategy.
Help design the architecture.
Implement the technology.
Audit the resulting systems.
Manage parts of the operation.
And provide ongoing services through AI-enabled platforms.
The relationship becomes more continuous.
The firm is moving from project-based expertise toward an integrated model in which advice, technology and operations reinforce one another.
The Risk Is That AI Changes KPMG’s Own Business
The transformation also creates a paradox.
KPMG is helping clients automate professional work while much of its own economic model has historically depended on professionals performing that work.
If AI dramatically reduces the amount of human labor required for certain services, the industry could face significant pressure on traditional billing models.
The answer cannot simply be to sell more hours.
The value proposition must move toward outcomes.
That means KPMG increasingly needs to demonstrate that it can help clients achieve measurable improvements in productivity, risk management, compliance, technology performance and business results.
AI makes that shift more urgent.
The firms that adapt fastest may be those that stop treating AI as a feature and start treating it as a redesign of the business model.
Why KPMG Matters
KPMG is not building a foundation model.
It is not competing with the companies developing the largest AI systems.
Its opportunity lies somewhere else.
The enterprise AI economy needs organizations capable of connecting technology with business processes, governance, regulation, cybersecurity and human decision-making.
That is the environment KPMG has spent decades operating in.
Its advantage is therefore not the AI model itself.
It is the combination of institutional trust, professional expertise, global relationships, regulatory knowledge and increasingly sophisticated technology infrastructure.
The company’s US$39.8 billion global revenue base gives it enormous scale from which to make that transition. (KPMG)
The question is what that organization looks like after the transformation is complete.
If the traditional professional services firm sold expertise by the hour, the emerging model could increasingly sell intelligence embedded in workflows.
Audit becomes more continuous.
Tax becomes more automated.
Consulting becomes more data-driven.
Managed services become more autonomous.
And AI becomes part of the operating infrastructure rather than an isolated technology project.
KPMG is betting that the professional services firm of the future will not simply advise companies about artificial intelligence.
It will help build, govern and operate the systems through which those companies use it.
The winning formula may be less about replacing professionals than about giving them better leverage — and ensuring that the machines know when to stop talking and let an expert take over.
Market Snapshot
Company: KPMG International
Founded: 1987
Headquarters: Amstelveen, Netherlands
Industry: Professional Services
Global Revenue FY2025: US$39.8 billion
Global Employees: 276,030
Countries & Territories: 142
FY2025 Audit Revenue: US$14.1 billion
FY2025 Advisory Revenue: US$16.4 billion
FY2025 Tax & Legal Revenue: US$9.3 billion
Global Chairman & CEO: Bill Thomas
Global Investment Program: US$4+ billion over four years
Fontes principais: KPMG International, resultados globais FY2025, materiais oficiais de AI, Global AI Pulse Q2 2026 e Managed Services Outlook 2026.
