QuantumBlack, AI by McKinsey vs Centric Consulting: full comparison for 2026
Quick verdict
QuantumBlack, AI by McKinsey (4.6/5) edges ahead of Centric Consulting (4.0/5) overall. QuantumBlack, AI by McKinsey is the better choice for large enterprises running AI as a CEO-level program. Centric Consulting is the stronger option for US mid-size firms wanting governed, practical AI adoption. 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 Centric Consulting: head-to-head summary
| Criterion | QuantumBlack, AI by McKinsey | Centric Consulting |
|---|---|---|
| Founded | 2009 | 1999 |
| HQ | London, UK (McKinsey HQ: New York, USA) | Dayton, USA |
| Team size | 1,000+ | 1,400 |
| Rating | 4.6 / 5 | 4.0 / 5 |
| Primary differentiator | Board-level strategy and change management backed by McKinsey's own AI engineering group | Practical AI adoption with acceptable-use policies and centers of excellence for mid-size firms |
| Pricing model | Project fees set per engagement; rates not published | Consulting fees per engagement; rates not published |
| Min. engagement | Not disclosed | Not disclosed |
| Primary tech stack | Kedro, Vizro, AWS | Azure, Microsoft Copilot, AWS |
| Industries served | Banking & insurance, Healthcare & life sciences, Consumer & retail, Manufacturing, Energy, Public sector | Insurance, Healthcare, Financial services, Manufacturing, Retail |
QuantumBlack, AI by McKinsey vs Centric Consulting: 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.
Centric Consulting
Centric Consulting was founded in 1999 with a remote workforce and is headquartered in Dayton, Ohio, with about 1,400 employees in the US and India. Its AI practice writes acceptable-use policies for generative AI tools, sets up AI centers of excellence, and builds custom solutions, with ready-made accelerators for insurance and healthcare. Expect practical adoption help for mid-size firms more than grand strategy.
Services and capabilities: QuantumBlack, AI by McKinsey vs Centric Consulting
| Capability | QuantumBlack, AI by McKinsey | Centric Consulting |
|---|---|---|
| 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 Centric Consulting
| Framework / platform | QuantumBlack, AI by McKinsey | Centric Consulting |
|---|---|---|
| EU AI Act | N/A | N/A |
| GDPR | N/A | N/A |
| NIST AI RMF | N/A | N/A |
| AWS | ✓ | ✓ |
| Azure | ✓ | ✓ |
| Google Cloud | ✓ | N/A |
| Databricks | ✓ | N/A |
| Snowflake | N/A | N/A |
Pricing comparison: QuantumBlack, AI by McKinsey vs Centric Consulting
| Criterion | QuantumBlack, AI by McKinsey | Centric Consulting |
|---|---|---|
| Minimum engagement | Not disclosed | Not disclosed |
| Engagement models | Strategy & roadmap engagement, Delivery team, Ongoing advisory | Strategy & roadmap engagement, Readiness assessment, Delivery team |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: QuantumBlack, AI by McKinsey vs Centric Consulting
| Dimension | QuantumBlack, AI by McKinsey | Centric Consulting |
|---|---|---|
| Best company size | Mid-market to enterprise | Mid-market to enterprise |
| Best industries | Banking & insurance, Healthcare & life sciences, Consumer & retail | Insurance, Healthcare, Financial services |
| 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. | Writing a generative AI acceptable-use policy and rolling out Copilot safely., Setting up an AI center of excellence in an insurer. |
| Typical project type | Strategy & roadmap engagement | Strategy & roadmap engagement |
QuantumBlack, AI by McKinsey vs Centric Consulting: 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 |
| Centric Consulting | |
|---|---|
| + | Acceptable-use policies and AI centers of excellence are standard deliverables |
| + | Industry accelerators for insurance and healthcare shorten the first project |
| + | Change management and staff training sit inside the same engagement |
| + | Priced and staffed for mid-size US companies |
| - | Limited reach outside the US and India |
| - | Less suited to research-heavy or novel model work |
| - | Rates and minimums are not published |
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 Centric Consulting?
A typical fit: writing a generative AI acceptable-use policy and rolling out Copilot safely.
Practical AI adoption with acceptable-use policies and centers of excellence for mid-size firms. Minimum engagement is not publicly disclosed. Works best with clients in Insurance, Healthcare, Financial services, Manufacturing, Retail.
Decision matrix: QuantumBlack, AI by McKinsey vs Centric Consulting
| 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 Centric Consulting (Not disclosed) |
| You need a large team across many countries | Centric Consulting |
Use case fit: QuantumBlack, AI by McKinsey vs Centric Consulting
| Use case | QuantumBlack, AI by McKinsey fit | Centric Consulting 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 |
| Writing a generative AI acceptable-use policy and rolling out Copilot safely. | Limited | Strong | Centric Consulting |
| Setting up an AI center of excellence in an insurer. | Limited | Strong | Centric Consulting |
Verdict: QuantumBlack, AI by McKinsey vs Centric Consulting
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.
Centric Consulting (4.0/5) is worth a look if you need setting up an AI center of excellence in an insurer. If your situation matches that, Centric Consulting is a competitive option.
Related comparisons
QuantumBlack, AI by McKinsey vs Centric Consulting FAQ
Is QuantumBlack, AI by McKinsey better than Centric Consulting?
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. Centric Consulting's strongest advantage: acceptable-use policies and AI centers of excellence are standard deliverables.
How do QuantumBlack, AI by McKinsey and Centric Consulting differ in pricing?
QuantumBlack, AI by McKinsey's pricing: project fees set per engagement; rates not published. Centric Consulting's pricing: consulting fees per engagement; 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 Centric Consulting?
Centric Consulting 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 Centric Consulting?
QuantumBlack, AI by McKinsey's primary differentiator is: board-level strategy and change management backed by McKinsey's own AI engineering group. Centric Consulting's primary differentiator is: practical AI adoption with acceptable-use policies and centers of excellence for mid-size firms. They also differ in team size (1,000+ vs 1,400), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Banking & insurance, Healthcare & life sciences vs Insurance, Healthcare).
Verify all details directly with each consultant before making a decision.