EY vs ML6: full comparison for 2026
Quick verdict
EY (4.2/5) edges ahead of ML6 (4.0/5) overall. EY is the better choice for enterprises building AI risk into existing controls. ML6 is the stronger option for benelux firms wanting advice from builders. The right choice depends on how independent you need the advice to be, your regulatory exposure, and your budget.
EY vs ML6: head-to-head summary
| Criterion | EY | ML6 |
|---|---|---|
| Founded | 1989 | 2013 |
| HQ | London, UK | Ghent, Belgium |
| Team size | ~400,000 | 140+ |
| Rating | 4.2 / 5 | 4.0 / 5 |
| Primary differentiator | AI risk work folded into existing technology risk and controls programs | Use-case discovery from engineers who also handle EU AI Act requirements |
| Pricing model | Engagement fees per scope; rates not published | Project fees; rates on request |
| Min. engagement | Not disclosed | Not disclosed |
| Primary tech stack | EU AI Act, NIST AI RMF, GDPR | EU AI Act, GDPR, Google Cloud |
| Industries served | Financial services, Insurance, Public sector, Energy, Consumer | Manufacturing, Media, Retail, Public sector, Financial services |
EY vs ML6: overview
EY
EY was formed by the 1989 merger of Ernst & Whinney and Arthur Young and employs about 400,000 people. Its advisory teams cover responsible AI, AI risk, and compliance programs, and its technology risk leaders have spoken publicly about how far real AI assurance still has to go. That candor is useful for buyers who want an honest view of what can be certified today. Like the rest of the Big Four, it sells implementation as well.
ML6
ML6 has been building AI in Ghent since 2013 and employs 140+ people in Belgium, Germany, and the Netherlands. Its strategy work covers ambition-setting workshops, use-case discovery, and EU AI Act questions, and OpenAI named it a services partner in June 2025. Most clients go on to build with ML6, so the advice is grounded in engineering reality but not neutral about who builds.
Services and capabilities: EY vs ML6
| Capability | EY | ML6 |
|---|---|---|
| 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: EY vs ML6
| Framework / platform | EY | ML6 |
|---|---|---|
| EU AI Act | ✓ | ✓ |
| GDPR | ✓ | ✓ |
| DORA | N/A | N/A |
| NIST AI RMF | ✓ | N/A |
| ISO/IEC 42001 | N/A | N/A |
| Azure | ✓ | N/A |
| AWS | N/A | N/A |
| Google Cloud | N/A | ✓ |
Pricing comparison: EY vs ML6
| Criterion | EY | ML6 |
|---|---|---|
| Minimum engagement | Not disclosed | Not disclosed |
| Engagement models | Fixed-scope assessment, Multi-use-case advisory, Audit or certification, Delivery team | Fixed-scope assessment, Delivery team |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: EY vs ML6
| Dimension | EY | ML6 |
|---|---|---|
| Best company size | Enterprise | Startup to mid-market |
| Best industries | Financial services, Insurance, Public sector | Manufacturing, Media, Retail |
| Best use cases | Adding AI risk to an existing controls framework., Responsible AI policies for a large insurer. | Use-case workshops for a Belgian or Dutch company., Checking feasibility before committing to a build. |
| Typical project type | Fixed-scope assessment | Fixed-scope assessment |
EY vs ML6: pros and cons
| EY | |
|---|---|
| + | Ties AI risk to controls frameworks finance teams already use |
| + | Realistic public view on the limits of AI assurance |
| + | Large global bench |
| - | Premium fees |
| - | Sells delivery alongside advice |
| - | Audit-client independence rules apply |
| ML6 | |
|---|---|
| + | Feasibility advice comes from people who build |
| + | EU regulation is routine in its projects |
| + | Strong Belgian and German client base |
| - | Advice usually leads into its own engineering work |
| - | OpenAI partnership may color model recommendations |
| - | Limited footprint outside the Benelux and Germany |
Who should choose EY?
A typical fit: adding AI risk to an existing controls framework.
AI risk work folded into existing technology risk and controls programs. Minimum engagement is not publicly disclosed. Works best with clients in Financial services, Insurance, Public sector, Energy, Consumer.
Who should choose ML6?
A typical fit: use-case workshops for a Belgian or Dutch company.
Use-case discovery from engineers who also handle EU AI Act requirements. Minimum engagement is not publicly disclosed. Works best with clients in Manufacturing, Media, Retail, Public sector, Financial services.
Decision matrix: EY vs ML6
| 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 | Neither lists cost modeling; ask for a sample |
| 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 | EY |
| You want the same firm to build what it recommends | Both can deliver |
| Your budget is at the lower end | Compare: EY (Not disclosed) vs ML6 (Not disclosed) |
| You need advisers in many countries at once | EY |
Use case fit: EY vs ML6
| Use case | EY fit | ML6 fit | Winner |
|---|---|---|---|
| Adding AI risk to an existing controls framework. | Strong | Limited | EY |
| Responsible AI policies for a large insurer. | Strong | Limited | EY |
| Use-case workshops for a Belgian or Dutch company. | Limited | Strong | ML6 |
| Checking feasibility before committing to a build. | Limited | Strong | ML6 |
Verdict: EY vs ML6
EY (4.2/5) is the stronger overall choice for most AI Advisory projects. AI risk work folded into existing technology risk and controls programs.
ML6 (4.0/5) is worth a look if you need checking feasibility before committing to a build. If your situation matches that, ML6 is a competitive option.
Related comparisons
EY vs ML6 FAQ
Is EY better than ML6?
EY (4.2/5) scores higher overall, but "better" depends on your use case. EY's strongest advantage: ties AI risk to controls frameworks finance teams already use. ML6's strongest advantage: feasibility advice comes from people who build.
How do EY and ML6 differ in pricing?
EY's pricing: engagement fees per scope; rates not published. ML6's pricing: project fees; rates on request. 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: EY or ML6?
EY 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 EY and ML6?
EY's primary differentiator is: AI risk work folded into existing technology risk and controls programs. ML6's primary differentiator is: use-case discovery from engineers who also handle EU AI Act requirements. They also differ in team size (~400,000 vs 140+), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Financial services, Insurance vs Manufacturing, Media).
Verify all details directly with each firm before making a decision.