QuantumBlack, AI by McKinsey vs Deloitte: full comparison for 2026
Quick verdict
QuantumBlack, AI by McKinsey (4.6/5) edges ahead of Deloitte (4.2/5) overall. QuantumBlack, AI by McKinsey is the better choice for large enterprises running AI as a CEO-level program. Deloitte is the stronger option for regulated enterprises needing AI governance with the strategy. The right choice depends on the size of your program, your budget, and whether you want the same firm to build what it recommends.
QuantumBlack, AI by McKinsey vs Deloitte: head-to-head summary
| Criterion | QuantumBlack, AI by McKinsey | Deloitte |
|---|---|---|
| Founded | 2009 | 1845 |
| HQ | London, UK (McKinsey HQ: New York, USA) | London, UK |
| Team size | 1,000+ | 460,000+ |
| Rating | 4.6 / 5 | 4.2 / 5 |
| Primary differentiator | Board-level strategy and change management backed by McKinsey's own AI engineering group | AI strategy backed by risk, audit, and regulatory teams under one roof |
| Pricing model | Project fees set per engagement; rates not published | Project and program fees; rates not published |
| Min. engagement | Not disclosed | Not disclosed |
| Primary tech stack | Kedro, Vizro, AWS | EU AI Act, NIST AI RMF, GDPR |
| Industries served | Banking & insurance, Healthcare & life sciences, Consumer & retail, Manufacturing, Energy, Public sector | Banking, Insurance, Healthcare, Government & public sector, Energy, Consumer |
QuantumBlack, AI by McKinsey vs Deloitte: overview
QuantumBlack, AI by McKinsey
QuantumBlack started in London in 2009 as an independent analytics firm and has been part of McKinsey & Company since 2015. McKinsey says it now has more than 1,000 technical practitioners, plus an R&D group, QuantumBlack Labs, of around 200 engineers, designers, and data scientists (per company website; independently unverifiable). A typical engagement pairs a strategy team that works with the chief executive and board with data scientists who build the first models, so the roadmap and the proof come from one firm. That access to the top of a company is the main reason to hire it. Price is the other side of it: fees follow McKinsey's own levels and are not published.
Deloitte
Deloitte traces its roots to London in 1845 and today employs more than 460,000 people across its member firms. Its AI strategy work runs through the consulting arm, often next to risk and regulatory teams, which is why it turns up most often in banking, insurance, health, and government programs. A company that has to show regulators how every AI system is governed will find that combination hard to match. Pace and price are the trade-off. Engagements are big, staffed with large teams, and priced accordingly.
Services and capabilities: QuantumBlack, AI by McKinsey vs Deloitte
| Capability | QuantumBlack, AI by McKinsey | Deloitte |
|---|---|---|
| Readiness assessment | ✗ | ✓ |
| Use-case prioritization | ✓ | ✗ |
| TCO / ROI modeling | ✗ | ✗ |
| AI governance & EU AI Act | ✓ | ✓ |
| Build vs. buy advice | ✗ | ✗ |
| Audit of live AI programs | ✗ | ✗ |
| Change management | ✓ | ✓ |
| Can build what it recommends | ✓ | ✓ |
Frameworks and platforms: QuantumBlack, AI by McKinsey vs Deloitte
| Framework / platform | QuantumBlack, AI by McKinsey | Deloitte |
|---|---|---|
| EU AI Act | N/A | ✓ |
| GDPR | N/A | ✓ |
| NIST AI RMF | N/A | ✓ |
| AWS | ✓ | ✓ |
| Azure | ✓ | ✓ |
| Google Cloud | ✓ | ✓ |
| Databricks | ✓ | N/A |
| Snowflake | N/A | N/A |
Pricing comparison: QuantumBlack, AI by McKinsey vs Deloitte
| Criterion | QuantumBlack, AI by McKinsey | Deloitte |
|---|---|---|
| Minimum engagement | Not disclosed | Not disclosed |
| Engagement models | Strategy & roadmap engagement, Delivery team, Ongoing advisory | Strategy & roadmap engagement, Readiness assessment, Delivery team, Ongoing advisory |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: QuantumBlack, AI by McKinsey vs Deloitte
| Dimension | QuantumBlack, AI by McKinsey | Deloitte |
|---|---|---|
| Best company size | Mid-market to enterprise | Enterprise |
| Best industries | Banking & insurance, Healthcare & life sciences, Consumer & retail | Banking, Insurance, Healthcare |
| Best use cases | Setting an enterprise AI agenda that the CEO and board will own., Redesigning operating models and roles around AI at a large company. | Building an AI governance framework that a regulator and audit committee will accept., Readiness assessments across a multinational bank or insurer. |
| Typical project type | Strategy & roadmap engagement | Strategy & roadmap engagement |
QuantumBlack, AI by McKinsey vs Deloitte: pros and cons
| QuantumBlack, AI by McKinsey | |
|---|---|
| + | Strategy teams work directly with chief executives and boards, which helps when AI spending needs sign-off at the very top |
| + | Change management and capability-building programs come from the same firm that wrote the strategy |
| + | Its own engineers build the first models, so feasibility gets tested before the roadmap is final |
| + | Maintains open-source tools (Kedro, Vizro) that show real engineering practice behind the advice |
| + | Industry depth across banking, health, consumer goods, and energy |
| - | Fees at McKinsey levels put it out of reach for most mid-market budgets |
| - | The firm that writes the roadmap also sells the follow-on work, so the plan may lean toward what McKinsey can deliver |
| - | Large programs mix partners with junior consultants, so confirm who will actually do the work |
| Deloitte | |
|---|---|
| + | Risk and regulatory specialists work alongside the strategy team, which suits banks, insurers, and health systems |
| + | Can staff programs in dozens of countries at once |
| + | Change management and workforce programs are long-established practices inside the firm |
| + | Years of work with regulators and audit committees make its governance advice easier to defend |
| - | Large teams and long timelines make it slow for a single use case |
| - | Fees are among the highest of the firms reviewed here |
| - | Auditor-independence rules limit what Deloitte may sell to its own audit clients, so check eligibility early |
Who should choose QuantumBlack, AI by McKinsey?
A typical fit: setting an enterprise AI agenda that the CEO and board will own.
Board-level strategy and change management backed by McKinsey's own AI engineering group. Minimum engagement is not publicly disclosed. Works best with clients in Banking & insurance, Healthcare & life sciences, Consumer & retail, Manufacturing, Energy, Public sector.
Who should choose Deloitte?
A typical fit: building an AI governance framework that a regulator and audit committee will accept.
AI strategy backed by risk, audit, and regulatory teams under one roof. Minimum engagement is not publicly disclosed. Works best with clients in Banking, Insurance, Healthcare, Government & public sector, Energy, Consumer.
Decision matrix: QuantumBlack, AI by McKinsey vs Deloitte
| Your situation | Recommended choice |
|---|---|
| Your board wants a costed, sequenced roadmap within a quarter | Neither lists cost modeling; ask for a sample roadmap |
| You already run AI that is missing its targets | Neither offers a separate audit; ask for a scoped review |
| Regulators will ask how each AI system is governed | Both cover AI governance |
| AI will change roles and processes for many staff | Both run change management |
| You want the strategy firm to build the result too | Both can deliver after the strategy |
| Your budget is at the lower end | Compare: QuantumBlack, AI by McKinsey (Not disclosed) vs Deloitte (Not disclosed) |
| You need a large team across many countries | Deloitte |
Use case fit: QuantumBlack, AI by McKinsey vs Deloitte
| Use case | QuantumBlack, AI by McKinsey fit | Deloitte fit | Winner |
|---|---|---|---|
| Setting an enterprise AI agenda that the CEO and board will own. | Strong | Limited | QuantumBlack, AI by McKinsey |
| Redesigning operating models and roles around AI at a large company. | Strong | Limited | QuantumBlack, AI by McKinsey |
| Building an AI governance framework that a regulator and audit committee will accept. | Limited | Strong | Deloitte |
| Readiness assessments across a multinational bank or insurer. | Limited | Strong | Deloitte |
Verdict: QuantumBlack, AI by McKinsey vs Deloitte
QuantumBlack, AI by McKinsey (4.6/5) is the stronger overall choice for most AI Strategy Consulting projects. Board-level strategy and change management backed by McKinsey's own AI engineering group.
Deloitte (4.2/5) is worth a look if you need readiness assessments across a multinational bank or insurer. If your situation matches that, Deloitte is a competitive option.
Related comparisons
QuantumBlack, AI by McKinsey vs Deloitte FAQ
Is QuantumBlack, AI by McKinsey better than Deloitte?
QuantumBlack, AI by McKinsey (4.6/5) scores higher overall, but "better" depends on your use case. QuantumBlack, AI by McKinsey's strongest advantage: strategy teams work directly with chief executives and boards, which helps when AI spending needs sign-off at the very top. Deloitte's strongest advantage: risk and regulatory specialists work alongside the strategy team, which suits banks, insurers, and health systems.
How do QuantumBlack, AI by McKinsey and Deloitte differ in pricing?
QuantumBlack, AI by McKinsey's pricing: project fees set per engagement; rates not published. Deloitte's pricing: project and program 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: QuantumBlack, AI by McKinsey or Deloitte?
Deloitte is the larger team and typically the better enterprise-scale choice. For very large programmes, verify team size and compliance coverage directly with each consultant before shortlisting.
What are the main differences between QuantumBlack, AI by McKinsey and Deloitte?
QuantumBlack, AI by McKinsey's primary differentiator is: board-level strategy and change management backed by McKinsey's own AI engineering group. Deloitte's primary differentiator is: AI strategy backed by risk, audit, and regulatory teams under one roof. They also differ in team size (1,000+ vs 460,000+), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Banking & insurance, Healthcare & life sciences vs Banking, Insurance).
Verify all details directly with each consultant before making a decision.