KPMG vs Slalom: full comparison for 2026
Quick verdict
KPMG (4.6/5) edges ahead of Slalom (3.8/5) overall. KPMG is the better choice for regulated firms needing audit-grade AI governance. Slalom is the stronger option for north American firms wanting local consultants. The right choice depends on how independent you need the advice to be, your regulatory exposure, and your budget.
KPMG vs Slalom: head-to-head summary
| Criterion | KPMG | Slalom |
|---|---|---|
| Founded | 1987 | 2001 |
| HQ | London, UK (KPMG International) | Seattle, USA |
| Team size | 275,000+ | 10,000+ |
| Rating | 4.6 / 5 | 3.8 / 5 |
| Primary differentiator | Governance and assurance depth, backed by its own ISO/IEC 42001-certified AI management system | Local-office consultants for AI governance and operating models |
| Pricing model | Engagement fees per scope; rates not published | Consulting fees; rates not published |
| Min. engagement | Not disclosed | Not disclosed |
| Primary tech stack | EU AI Act, ISO/IEC 42001, NIST AI RMF | AWS, Azure, Google Cloud |
| Industries served | Banking, Insurance, Public sector, Healthcare, Energy, Manufacturing | Financial services, Healthcare, Retail, Public sector |
KPMG vs Slalom: overview
KPMG
KPMG was formed in 1987 through the merger of Peat Marwick International and Klynveld Main Goerdeler, and its member firms employ around 275,000 people. In December 2025 KPMG International announced ISO/IEC 42001 certification for its own AI management system, audited by Schellman; member firms in Australia, Spain, India, and the US had certified earlier. Its Trusted AI approach covers governance design, risk classification under the EU AI Act, controls testing, and assurance. For a CFO or chief risk officer who needs advice that an audit committee will accept, few firms have a larger bench. Auditor-independence rules can bar it from advising its own audit clients. Check that first.
Slalom
Slalom has more than 10,000 employees in over 50 offices and was founded in Seattle in 2001. Its AI and data strategists work on governance and operating models, and a new chief AI officer arrived in August 2026. Close ties with the major cloud and data vendors mean its advice usually points toward those platforms.
Services and capabilities: KPMG vs Slalom
| Capability | KPMG | Slalom |
|---|---|---|
| Readiness assessment | ✓ | ✗ |
| Use-case prioritization | ✗ | ✗ |
| TCO / ROI modeling | ✓ | ✗ |
| AI governance & EU AI Act | ✓ | ✓ |
| Build vs. buy advice | ✗ | ✗ |
| Independent audit or assurance | ✓ | ✗ |
| Roadmap any vendor can implement | ✗ | ✗ |
| Delivery capability after advice | ✓ | ✓ |
Frameworks and platforms: KPMG vs Slalom
| Framework / platform | KPMG | Slalom |
|---|---|---|
| EU AI Act | ✓ | N/A |
| GDPR | ✓ | N/A |
| DORA | ✓ | N/A |
| NIST AI RMF | ✓ | N/A |
| ISO/IEC 42001 | ✓ | N/A |
| Azure | ✓ | ✓ |
| AWS | N/A | ✓ |
| Google Cloud | N/A | ✓ |
Pricing comparison: KPMG vs Slalom
| Criterion | KPMG | Slalom |
|---|---|---|
| Minimum engagement | Not disclosed | Not disclosed |
| Engagement models | Fixed-scope assessment, Multi-use-case advisory, Audit or certification, Delivery team | Multi-use-case advisory, Delivery team |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: KPMG vs Slalom
| Dimension | KPMG | Slalom |
|---|---|---|
| Best company size | Enterprise | Enterprise |
| Best industries | Banking, Insurance, Public sector | Financial services, Healthcare, Retail |
| Best use cases | Designing an AI governance framework that an audit committee will sign off., Classifying an AI portfolio under the EU AI Act across several countries. | AI governance for a North American company., Operating-model changes for AI. |
| Typical project type | Fixed-scope assessment | Multi-use-case advisory |
KPMG vs Slalom: pros and cons
| KPMG | |
|---|---|
| + | Runs its own certified AI management system, so it advises from first-hand experience of ISO/IEC 42001 |
| + | Risk, audit, and regulatory specialists work in one network |
| + | Can carry governance work across dozens of countries |
| + | Assurance work is set up to satisfy audit committees and regulators |
| - | Auditor-independence rules may stop it advising its own audit clients |
| - | Fees and team sizes suit large organizations more than mid-size ones |
| - | The same network sells implementation, so ask how advice and delivery are separated |
| Slalom | |
|---|---|
| + | Local teams for on-site work |
| + | Governance and operating-model experience |
| + | Can build afterward |
| - | Advice leans toward its partner platforms |
| - | Limited EU regulatory depth |
| - | New AI leadership still settling in |
Who should choose KPMG?
A typical fit: designing an AI governance framework that an audit committee will sign off.
Governance and assurance depth, backed by its own ISO/IEC 42001-certified AI management system. Minimum engagement is not publicly disclosed. Works best with clients in Banking, Insurance, Public sector, Healthcare, Energy, Manufacturing.
Who should choose Slalom?
A typical fit: AI governance for a North American company.
Local-office consultants for AI governance and operating models. Minimum engagement is not publicly disclosed. Works best with clients in Financial services, Healthcare, Retail, Public sector.
Decision matrix: KPMG vs Slalom
| Your situation | Recommended choice |
|---|---|
| You want advice with no build contract attached | Neither; write the build as a separate decision |
| Finance needs run costs before approving anything | KPMG |
| Some of your use cases may be high-risk under the EU AI Act | Both cover AI Act classification |
| You need an outside check on a system already built | KPMG |
| You want the same firm to build what it recommends | Both can deliver |
| Your budget is at the lower end | Compare: KPMG (Not disclosed) vs Slalom (Not disclosed) |
| You need advisers in many countries at once | KPMG |
Use case fit: KPMG vs Slalom
| Use case | KPMG fit | Slalom fit | Winner |
|---|---|---|---|
| Designing an AI governance framework that an audit committee will sign off. | Strong | Limited | KPMG |
| Classifying an AI portfolio under the EU AI Act across several countries. | Strong | Limited | KPMG |
| AI governance for a North American company. | Limited | Strong | Slalom |
| Operating-model changes for AI. | Limited | Strong | Slalom |
Verdict: KPMG vs Slalom
KPMG (4.6/5) is the stronger overall choice for most AI Advisory projects. Governance and assurance depth, backed by its own ISO/IEC 42001-certified AI management system.
Slalom (3.8/5) is worth a look if you need operating-model changes for AI. If your situation matches that, Slalom is a competitive option.
Related comparisons
KPMG vs Slalom FAQ
Is KPMG better than Slalom?
KPMG (4.6/5) scores higher overall, but "better" depends on your use case. KPMG's strongest advantage: runs its own certified AI management system, so it advises from first-hand experience of ISO/IEC 42001. Slalom's strongest advantage: local teams for on-site work.
How do KPMG and Slalom differ in pricing?
KPMG's pricing: engagement fees per scope; rates not published. Slalom's pricing: consulting fees; rates not published. Any hourly bands shown come from Clutch, not a published rate card, so a scoping call is still needed for a project quote.
Which is better for enterprise: KPMG or Slalom?
KPMG is the larger team and typically the better enterprise-scale choice. For very large programmes, verify team size and compliance coverage directly with each firm before shortlisting.
What are the main differences between KPMG and Slalom?
KPMG's primary differentiator is: governance and assurance depth, backed by its own ISO/IEC 42001-certified AI management system. Slalom's primary differentiator is: local-office consultants for AI governance and operating models. They also differ in team size (275,000+ vs 10,000+), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Banking, Insurance vs Financial services, Healthcare).
Verify all details directly with each firm before making a decision.