QuantumBlack, AI by McKinsey vs Tensorway: full comparison for 2026
Quick verdict
QuantumBlack, AI by McKinsey (4.6/5) edges ahead of Tensorway (4.4/5) overall. QuantumBlack, AI by McKinsey is the better choice for large enterprises running AI as a CEO-level program. Tensorway is the stronger option for mid-market leaders wanting a costed AI roadmap fast. 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 Tensorway: head-to-head summary
| Criterion | QuantumBlack, AI by McKinsey | Tensorway |
|---|---|---|
| Founded | 2009 | 2019 |
| HQ | London, UK (McKinsey HQ: New York, USA) | Alicante, Spain |
| Team size | 1,000+ | 50+ |
| Rating | 4.6 / 5 | 4.4 / 5 |
| Primary differentiator | Board-level strategy and change management backed by McKinsey's own AI engineering group | A 3–6 week strategy engagement that ends in a sequenced, costed roadmap the same team can build |
| Pricing model | Project fees set per engagement; rates not published | Scoped to complexity with no published rates; strategy engagements usually run 3–6 weeks |
| Min. engagement | Not disclosed | Not disclosed |
| Primary tech stack | Kedro, Vizro, AWS | EU AI Act, GDPR, NIST AI RMF |
| Industries served | Banking & insurance, Healthcare & life sciences, Consumer & retail, Manufacturing, Energy, Public sector | Financial services, Private equity, Legal, Retail & e-commerce, Education, Media |
QuantumBlack, AI by McKinsey vs Tensorway: 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.
Tensorway
Tensorway is an AI consulting and engineering firm founded in 2019 in Alicante, Spain, with a team of more than 50. Strategy work here is short. Engagements usually take three to six weeks and end in a roadmap that prices and orders each use case, with its risks named. If a company already runs AI that isn't paying off, it can buy a separate solution audit instead, which looks at data readiness and the causes of underperformance and estimates the effort to fix them. Its consultants draw on a software engineering track record of more than twenty years, and many clients move on to development with the same team. The case it leads with is a Swedish private equity fund whose AI agent system cut deal-sourcing time by 80% and screens 5,000+ opportunities in hours (per company website; independently unverifiable). It publishes no rates and promises no return on investment (ROI) up front; estimates come from the client's own data and goals.
Services and capabilities: QuantumBlack, AI by McKinsey vs Tensorway
| Capability | QuantumBlack, AI by McKinsey | Tensorway |
|---|---|---|
| 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 Tensorway
| Framework / platform | QuantumBlack, AI by McKinsey | Tensorway |
|---|---|---|
| EU AI Act | N/A | ✓ |
| GDPR | N/A | ✓ |
| NIST AI RMF | N/A | ✓ |
| AWS | ✓ | N/A |
| Azure | ✓ | N/A |
| Google Cloud | ✓ | N/A |
| Databricks | ✓ | N/A |
| Snowflake | N/A | ✓ |
Pricing comparison: QuantumBlack, AI by McKinsey vs Tensorway
| Criterion | QuantumBlack, AI by McKinsey | Tensorway |
|---|---|---|
| Minimum engagement | Not disclosed | Not disclosed |
| Engagement models | Strategy & roadmap engagement, Delivery team, Ongoing advisory | Strategy & roadmap engagement, AI solution audit, Ongoing advisory, Delivery team |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: QuantumBlack, AI by McKinsey vs Tensorway
| Dimension | QuantumBlack, AI by McKinsey | Tensorway |
|---|---|---|
| Best company size | Mid-market to enterprise | Startup to mid-market |
| Best industries | Banking & insurance, Healthcare & life sciences, Consumer & retail | Financial services, Private equity, Legal |
| 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 a sequenced AI roadmap with cost and risk per stage before a budget cycle., Auditing an AI program that is live but missing its targets. |
| Typical project type | Strategy & roadmap engagement | Strategy & roadmap engagement |
QuantumBlack, AI by McKinsey vs Tensorway: 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 |
| Tensorway | |
|---|---|
| + | Strategy work is time-boxed at three to six weeks, so a board sees a roadmap within one quarter |
| + | The roadmap prices each stage and names its risks, which gives finance something to approve or cut line by line |
| + | Offers a separate audit for AI programs that are live and underperforming, a case many strategy firms don't scope on its own |
| + | The same team can build what it recommends, so nobody has to brief a second vendor on the plan |
| + | Will tell you when a use case isn't worth building and drop it from the plan |
| + | Covers EU AI Act scoping and GDPR rules on automated decisions inside the strategy work |
| - | Much smaller than the big strategy houses on organizational design and change management for thousands of staff |
| - | No published rates or project minimum, so the budget stays unknown until scoping |
| - | No certifications or named cloud-partner tier appear on its pages |
| - | Recognition logos on its site (Clutch, Fortune, and others) come with no detail you can check |
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 Tensorway?
A typical fit: building a sequenced AI roadmap with cost and risk per stage before a budget cycle.
A 3–6 week strategy engagement that ends in a sequenced, costed roadmap the same team can build. Minimum engagement is not publicly disclosed. Works best with clients in Financial services, Private equity, Legal, Retail & e-commerce, Education, Media.
Decision matrix: QuantumBlack, AI by McKinsey vs Tensorway
| Your situation | Recommended choice |
|---|---|
| Your board wants a costed, sequenced roadmap within a quarter | Tensorway |
| You already run AI that is missing its targets | Tensorway |
| Regulators will ask how each AI system is governed | Both cover AI governance |
| AI will change roles and processes for many staff | QuantumBlack, AI by McKinsey |
| 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 Tensorway (Not disclosed) |
| You need a large team across many countries | QuantumBlack, AI by McKinsey |
Use case fit: QuantumBlack, AI by McKinsey vs Tensorway
| Use case | QuantumBlack, AI by McKinsey fit | Tensorway 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 a sequenced AI roadmap with cost and risk per stage before a budget cycle. | Limited | Strong | Tensorway |
| Auditing an AI program that is live but missing its targets. | Limited | Strong | Tensorway |
Verdict: QuantumBlack, AI by McKinsey vs Tensorway
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.
Tensorway (4.4/5) is worth a look if you need auditing an AI program that is live but missing its targets. If your situation matches that, Tensorway is a competitive option.
Related comparisons
QuantumBlack, AI by McKinsey vs Tensorway FAQ
Is QuantumBlack, AI by McKinsey better than Tensorway?
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. Tensorway's strongest advantage: strategy work is time-boxed at three to six weeks, so a board sees a roadmap within one quarter.
How do QuantumBlack, AI by McKinsey and Tensorway differ in pricing?
QuantumBlack, AI by McKinsey's pricing: project fees set per engagement; rates not published. Tensorway's pricing: scoped to complexity with no published rates; strategy engagements usually run 3–6 weeks. 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 Tensorway?
QuantumBlack, AI by McKinsey 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 Tensorway?
QuantumBlack, AI by McKinsey's primary differentiator is: board-level strategy and change management backed by McKinsey's own AI engineering group. Tensorway's primary differentiator is: a 3–6 week strategy engagement that ends in a sequenced, costed roadmap the same team can build. They also differ in team size (1,000+ vs 50+), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Banking & insurance, Healthcare & life sciences vs Financial services, Private equity).
Verify all details directly with each consultant before making a decision.