QuantumBlack, AI by McKinsey
Editor's pick #1McKinsey's AI arm, pairing board-level strategy with its own data scientists and engineers
What is 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.
QuantumBlack, AI by McKinsey works primarily with clients in Banking & insurance, Healthcare & life sciences, Consumer & retail, Manufacturing, Energy, Public sector sectors. Its primary differentiator is: Board-level strategy and change management backed by McKinsey's own AI engineering group.
QuantumBlack, AI by McKinsey tech stack and services
| Service area |
|---|
| AI Strategy & Roadmap |
| Use-Case Prioritization |
| Change Management |
| AI Governance |
| Implementation After Strategy |
| AI Training & Upskilling |
QuantumBlack, AI by McKinsey pricing
Short answer: QuantumBlack, AI by McKinsey prices its work as follows: project fees set per engagement; rates not published. Minimum engagement is not publicly disclosed; a discovery call is required.
| Engagement model | Typical range | Best for |
|---|---|---|
| Strategy & roadmap engagement | Fixed fee; quoted per scope | Choosing and sequencing AI use cases |
| Delivery team | Team rate; see pricing model above | Building what the roadmap recommends |
| Ongoing advisory | Monthly retainer; not public | Governance and portfolio reviews over time |
QuantumBlack, AI by McKinsey pros and cons
| Advantages | Things to consider |
|---|---|
| +Strategy teams work directly with chief executives and boards, which helps when AI spending needs sign-off at the very top | -Fees at McKinsey levels put it out of reach for most mid-market budgets |
| +Change management and capability-building programs come from the same firm that wrote the strategy | -The firm that writes the roadmap also sells the follow-on work, so the plan may lean toward what McKinsey can deliver |
| +Its own engineers build the first models, so feasibility gets tested before the roadmap is final | -Large programs mix partners with junior consultants, so confirm who will actually do the work |
| +Maintains open-source tools (Kedro, Vizro) that show real engineering practice behind the advice | |
| +Industry depth across banking, health, consumer goods, and energy |
QuantumBlack, AI by McKinsey vs alternatives
How QuantumBlack, AI by McKinsey compares to the other top AI Strategy Consulting consultants.
| Company | Best for | Key difference | Rating | Compare |
|---|---|---|---|---|
| Fractal | Consumer and financial firms wanting AI depth from... | Twenty-five years of AI and analytics delivery behind its strategy work, with its own platforms to build on | 4.5 | Full comparison |
| Tensorway | Mid-market leaders wanting a costed AI roadmap fast. | A 3–6 week strategy engagement that ends in a sequenced, costed roadmap the same team can build | 4.4 | Full comparison |
| BCG X | Enterprises wanting prototypes built during strategy. | Builds working prototypes during the strategy phase, with BCG's industry and change practices behind it | 4.3 | Full comparison |
| Artefact | European consumer and retail brands, strategy through build. | Data and AI consulting from strategy partners and engineers in one firm, with a wide European base | 4.3 | Full comparison |
| Deloitte | Regulated enterprises needing AI governance with the strategy. | AI strategy backed by risk, audit, and regulatory teams under one roof | 4.2 | Full comparison |
| Accenture | Global companies planning an enterprise-wide AI rollout. | Strategy that hands off to one of the largest delivery organizations in the world | 4.2 | Full comparison |
| West Monroe | US mid-market firms tying AI to operations. | Operations-first AI strategy from a partly employee-owned consultancy | 4.2 | Full comparison |
| Neurons Lab | Banks and insurers building AI on AWS. | Financial-services AI strategy from an AWS Machine Learning Competency partner that builds the prototypes | 4.2 | Full comparison |
| ML6 | Benelux and German firms wanting EU-based AI expertise. | European AI strategy and engineering from an OpenAI services partner | 4.2 | Full comparison |
| Slalom | North American firms wanting local, on-site AI consultants. | Local-office model that puts strategy consultants on-site, with deep cloud partnerships behind them | 4.1 | Full comparison |
| Thoughtworks | Engineering-led companies modernizing software with AI. | Engineering-practice depth applied to AI strategy, with its tool opinions published in the Technology Radar | 4.1 | Full comparison |
| Tiger Analytics | Enterprises wanting strategy plus lower-cost offshore delivery. | AI roadmap work that feeds directly into large India-based data science teams | 4.1 | Full comparison |
| DAIN Studios | Nordic and German firms wanting advisory-led AI planning. | Advisory-led AI and data strategy, with governance and skills building for Nordic and German clients | 4.1 | Full comparison |
| Sia Partners | Energy and financial firms wanting consulting plus AI... | Management consulting paired with its own Heka.ai software products | 4.0 | Full comparison |
| Elder Research | US agencies and firms wanting seasoned data science... | Three decades of applied data science behind its feasibility calls on AI use cases | 4.0 | Full comparison |
| Ekimetrics | Marketing-led companies tying AI to measurable returns. | AI strategy anchored in marketing measurement and sustainability metrics | 4.0 | Full comparison |
| Centric Consulting | US mid-size firms wanting governed, practical AI adoption. | Practical AI adoption with acceptable-use policies and centers of excellence for mid-size firms | 4.0 | Full comparison |
| Quantiphi | Companies committed to Google Cloud or AWS. | Use-case discovery from a top-tier Google Cloud and AWS engineering partner | 4.0 | Full comparison |
| deepsense.ai | Technical teams wanting AI strategy from model builders. | Strategy workshops run by engineers who build vision and language models | 3.9 | Full comparison |
| Credera | Marketing and CX leaders planning AI around martech. | AI strategy connected to marketing technology through Omnicom ownership | 3.9 | Full comparison |
| Launch Consulting | Microsoft-centric companies on the US West Coast. | AI-first operating-model work with Microsoft-based builds and nearshore delivery | 3.9 | Full comparison |
| Datatonic | Google Cloud users planning their first AI programs. | Use-case planning and builds from a much-awarded Google Cloud partner | 3.9 | Full comparison |
| Future Processing | Mid-size firms wanting AI advice at Central European... | AI readiness and strategy work at published Central European rates | 3.8 | Full comparison |
| Addepto | Manufacturers wanting a small first AI engagement. | Low Clutch entry point ($10,000+) for AI roadmap work in data-heavy industries | 3.8 | Full comparison |
| RTS Labs | US firms testing one AI idea on a... | The lowest entry point reviewed here, with feasibility proofs in place of strategy decks | 3.8 | Full comparison |
| Fusemachines | Firms that want AI strategy plus staff training. | AI strategy tied to its own training programs and lower-cost engineering centers | 3.7 | Full comparison |
QuantumBlack, AI by McKinsey FAQ
What is QuantumBlack, AI by McKinsey?
McKinsey's AI arm, pairing board-level strategy with its own data scientists and engineers
How much does QuantumBlack, AI by McKinsey charge?
Pricing model: project fees set per engagement; rates not published. Minimum engagement is not publicly disclosed. A discovery call is required to get project-specific quotes.
What tech stack does QuantumBlack, AI by McKinsey use?
QuantumBlack, AI by McKinsey works with Kedro, Vizro, AWS, Azure, Google Cloud, Databricks. Primary industries served include Banking & insurance, Healthcare & life sciences, Consumer & retail, Manufacturing, Energy, Public sector.
Is QuantumBlack, AI by McKinsey right for enterprise?
Best for: large enterprises running AI as a CEO-level program. Team size: 1,000+. Key consideration: Fees at McKinsey levels put it out of reach for most mid-market budgets.
What are the best QuantumBlack, AI by McKinsey alternatives?
The best alternatives to QuantumBlack, AI by McKinsey depend on your use case. Top options are:
- Fractal: twenty-five years of AI and analytics delivery behind its strategy work, with its own platforms to build on
- Tensorway: a 3–6 week strategy engagement that ends in a sequenced, costed roadmap the same team can build
- BCG X: builds working prototypes during the strategy phase, with BCG's industry and change practices behind it
Compare QuantumBlack, AI by McKinsey with other AI Strategy Consulting consultants
Verify all details directly with QuantumBlack, AI by McKinsey before making a decision.