KPMG vs Andersen: full comparison for 2026
Quick verdict
KPMG (4.1/5) edges ahead of Andersen (4.0/5) overall. KPMG is the better choice for enterprises wanting named AI products alongside Big Four advisory. Andersen is the stronger option for enterprises wanting AI advisory paired with broad platform engineering. The right choice depends on your project size, budget, and required tech stack.
KPMG vs Andersen: head-to-head summary
| Criterion | KPMG | Andersen |
|---|---|---|
| Founded | 1987 | 2007 |
| HQ | London, United Kingdom | Warsaw, Poland |
| Team size | 251,000-275,000 | 3,500+ |
| Rating | 4.1 / 5 | 4.0 / 5 |
| Primary differentiator | Named AI products, aIQ and Mystro, rather than purely bespoke advisory work | 3,500-plus specialists across 20 global offices with a named AI advisory practice |
| Pricing model | Retainer, enterprise contracting | Dedicated team or retainer |
| Min. engagement | Not disclosed | Not disclosed |
| Primary tech stack | Python, AWS, Azure | Python, .NET, Java |
| Industries served | Financial services, Healthcare, Manufacturing, Government | Financial services, Healthcare, Logistics, Automotive |
KPMG vs Andersen: overview
KPMG
KPMG formed in 1987 from the merger of Peat Marwick International and Klynveld Main Goerdeler, with a lineage tracing back to 1897, and runs today out of London. Headcount estimates land somewhere between roughly 251,875 and 275,288 depending on the reporting period cited. Its AI service line includes named products, aIQ and Mystro, aimed at AI transformation and digital labor optimization, which is more productized than most Big Four peers, though the firm hasn't disclosed how much staff sits specifically inside the AI practice.
Andersen
Andersen was founded in 2007 and is headquartered in Warsaw, Poland, running more than 3,500 specialists across 20 office locations and 16 development centers globally. Its named AI and data practice spans advisory, machine learning, data engineering, and robotic process integration, sitting on top of a broader stack that covers .NET, Java, Python, PHP, and Go. Its client industries run through financial services, healthcare, logistics, automotive, and media.
Services and capabilities: KPMG vs Andersen
| Capability | KPMG | Andersen |
|---|---|---|
| AI strategy consulting | ✓ | ✓ |
| Generative AI | ✗ | ✗ |
| Machine learning | ✓ | ✓ |
| Data engineering | ✗ | ✓ |
| MLOps | ✗ | ✗ |
| Fixed-price projects | ✗ | ✗ |
| Dedicated team model | ✓ | ✓ |
Tech stack comparison: KPMG vs Andersen
| Framework / platform | KPMG | Andersen |
|---|---|---|
| Python | ✓ | ✓ |
| AWS | ✓ | ✓ |
| Azure | ✓ | ✓ |
| Google Cloud | ✓ | N/A |
| Kubernetes | ✓ | N/A |
| LangChain | N/A | N/A |
| PyTorch | N/A | N/A |
Pricing comparison: KPMG vs Andersen
| Criterion | KPMG | Andersen |
|---|---|---|
| Minimum engagement | Not disclosed | Not disclosed |
| Engagement models | Retainer, Dedicated team | Dedicated team, Retainer |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: KPMG vs Andersen
| Dimension | KPMG | Andersen |
|---|---|---|
| Best company size | Mid-market to enterprise | Startup to mid-market |
| Best industries | Financial services, Healthcare, Manufacturing | Financial services, Healthcare, Logistics |
| Best use cases | Adopting a named, productized AI tool instead of commissioning a fully bespoke build., Running an AI workforce transformation program alongside existing KPMG advisory work. | Running an AI advisory initiative that needs to plug into an existing multi-technology enterprise stack., Adding robotic process integration alongside an AI advisory engagement. |
| Typical project type | Retainer | Dedicated team |
KPMG vs Andersen: pros and cons
| KPMG | |
|---|---|
| + | Scale at 251,000-plus people supports the largest enterprise engagements. |
| + | Named, productized AI tools give buyers something concrete to evaluate instead of a generic pitch. |
| + | Nearly 130 years of institutional history dating back to 1897. |
| + | A London headquarters simplifies EU and UK contracting. |
| - | Reported headcount swings by roughly 25,000 depending on which source and period you check |
| - | Big Four pricing and minimum engagement sizes rule out most small and mid-size buyers |
| Andersen | |
|---|---|
| + | A large global footprint, 20 offices and 16 development centers, supports concurrent enterprise programs. |
| + | The named AI and data practice isn't just a marketing add-on to broader software services. |
| + | Nearly two decades of software delivery history across multiple technology stacks. |
| + | Vertical coverage spans financial services, healthcare, logistics, and automotive. |
| - | AI advisory is one practice area within a much larger, multi-stack engineering business |
| - | Scale typically means a more formal sales and onboarding process than smaller agencies |
Who should choose KPMG?
A typical fit: adopting a named, productized AI tool instead of commissioning a fully bespoke build.
Named AI products, aIQ and Mystro, rather than purely bespoke advisory work. Minimum engagement is not publicly disclosed. Works best with clients in Financial services, Healthcare, Manufacturing, Government.
Who should choose Andersen?
A typical fit: running an AI advisory initiative that needs to plug into an existing multi-technology enterprise stack.
3,500-plus specialists across 20 global offices with a named AI advisory practice. Minimum engagement is not publicly disclosed. Works best with clients in Financial services, Healthcare, Logistics, Automotive.
Decision matrix: KPMG vs Andersen
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | Both offer fixed-price models |
| You need a large dedicated team for an ongoing programme | KPMG |
| Your budget is at the lower end | Compare: KPMG (Not disclosed) vs Andersen (Not disclosed) |
| You need specialist depth in a specific vertical | KPMG |
| You need staff augmentation or team extension | Neither; consider alternatives that offer staff aug |
| You need consulting before committing to a build | KPMG |
Use case fit: KPMG vs Andersen
| Use case | KPMG fit | Andersen fit | Winner |
|---|---|---|---|
| Adopting a named, productized AI tool instead of commissioning a fully bespoke build. | Strong | Limited | KPMG |
| Running an AI workforce transformation program alongside existing KPMG advisory work. | Strong | Strong | Both equally |
| Running an AI advisory initiative that needs to plug into an existing multi-technology enterprise stack. | Strong | Strong | Both equally |
| Adding robotic process integration alongside an AI advisory engagement. | Limited | Strong | Andersen |
| Fixed-price project | Limited | Limited | Both equally |
| Dedicated team model | Limited | Limited | Both equally |
Verdict: KPMG vs Andersen
KPMG (4.1/5) is the stronger overall choice for most AI Consulting projects. Named AI products, aIQ and Mystro, rather than purely bespoke advisory work.
Andersen (4.0/5) is worth a look if you need adding robotic process integration alongside an AI advisory engagement. If your situation matches that, Andersen is a competitive option.
Related comparisons
KPMG vs Andersen FAQ
Is KPMG better than Andersen?
KPMG (4.1/5) scores higher overall, but "better" depends on your use case. KPMG's strongest advantage: scale at 251,000-plus people supports the largest enterprise engagements. Andersen's strongest advantage: a large global footprint, 20 offices and 16 development centers, supports concurrent enterprise programs.
How do KPMG and Andersen differ in pricing?
KPMG uses retainer, enterprise contracting pricing. Andersen uses dedicated team or retainer pricing. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: KPMG or Andersen?
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 agency before shortlisting.
What are the main differences between KPMG and Andersen?
KPMG's primary differentiator is: named AI products, aIQ and Mystro, rather than purely bespoke advisory work. Andersen's primary differentiator is: 3,500-plus specialists across 20 global offices with a named AI advisory practice. They also differ in team size (251,000-275,000 vs 3,500+), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Financial services, Healthcare vs Financial services, Healthcare).
Verify all details directly with each agency before making a decision.