QuantumBlack, AI by McKinsey vs deepsense.ai: full comparison for 2026
Quick verdict
QuantumBlack, AI by McKinsey (4.6/5) edges ahead of deepsense.ai (3.9/5) overall. QuantumBlack, AI by McKinsey is the better choice for large enterprises running AI as a CEO-level program. deepsense.ai is the stronger option for technical teams wanting AI strategy from model builders. 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 deepsense.ai: head-to-head summary
| Criterion | QuantumBlack, AI by McKinsey | deepsense.ai |
|---|---|---|
| Founded | 2009 | 2014 |
| HQ | London, UK (McKinsey HQ: New York, USA) | Warsaw, Poland |
| Team size | 1,000+ | 120+ |
| Rating | 4.6 / 5 | 3.9 / 5 |
| Primary differentiator | Board-level strategy and change management backed by McKinsey's own AI engineering group | Strategy workshops run by engineers who build vision and language models |
| Pricing model | Project fees set per engagement; rates not published | $100–$149/hr (Clutch band); project-based |
| Min. engagement | Not disclosed | $25,000+ (Clutch) |
| Primary tech stack | Kedro, Vizro, AWS | Python, PyTorch, AWS |
| Industries served | Banking & insurance, Healthcare & life sciences, Consumer & retail, Manufacturing, Energy, Public sector | Retail, Manufacturing, Financial services, Healthcare, Media |
QuantumBlack, AI by McKinsey vs deepsense.ai: 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.
deepsense.ai
deepsense.ai was founded in 2014 in Warsaw and has an office in Palo Alto, with about 120 AI specialists, several of them Kaggle competition winners (per company website; independently unverifiable). It sells AI strategy consulting and workshops, though most of its work is engineering: computer vision, language models, and predictive systems. Clutch lists rates of $100–$149 an hour and a $25,000+ minimum project. That puts it at the top end for a Central European firm.
Services and capabilities: QuantumBlack, AI by McKinsey vs deepsense.ai
| Capability | QuantumBlack, AI by McKinsey | deepsense.ai |
|---|---|---|
| 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 deepsense.ai
| Framework / platform | QuantumBlack, AI by McKinsey | deepsense.ai |
|---|---|---|
| EU AI Act | N/A | N/A |
| GDPR | N/A | N/A |
| NIST AI RMF | N/A | N/A |
| AWS | ✓ | ✓ |
| Azure | ✓ | ✓ |
| Google Cloud | ✓ | ✓ |
| Databricks | ✓ | N/A |
| Snowflake | N/A | N/A |
Pricing comparison: QuantumBlack, AI by McKinsey vs deepsense.ai
| Criterion | QuantumBlack, AI by McKinsey | deepsense.ai |
|---|---|---|
| Minimum engagement | Not disclosed | $25,000+ (Clutch) |
| Engagement models | Strategy & roadmap engagement, Delivery team, Ongoing advisory | Strategy & roadmap engagement, Delivery team |
| Rate transparency | Not public | Minimum disclosed |
| Price tier | Mid-market | Mid-market |
Target audience comparison: QuantumBlack, AI by McKinsey vs deepsense.ai
| Dimension | QuantumBlack, AI by McKinsey | deepsense.ai |
|---|---|---|
| Best company size | Mid-market to enterprise | Startup to mid-market |
| Best industries | Banking & insurance, Healthcare & life sciences, Consumer & retail | Retail, Manufacturing, 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. | Workshops to pick a first computer vision or language model project., Technical feasibility reviews for an AI product idea. |
| Typical project type | Strategy & roadmap engagement | Strategy & roadmap engagement |
QuantumBlack, AI by McKinsey vs deepsense.ai: 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 |
| deepsense.ai | |
|---|---|
| + | Workshops are run by people who build models, so feasibility advice is concrete |
| + | Strong research background in computer vision and language models |
| + | Offers AI training for client teams |
| + | Published Clutch rates make budgeting easier |
| - | Strategy is a small part of an engineering-led business |
| - | Higher Clutch rate band than most Polish peers |
| - | No change-management practice |
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 deepsense.ai?
A typical fit: workshops to pick a first computer vision or language model project.
Strategy workshops run by engineers who build vision and language models. Minimum engagement starts at $25,000+ (Clutch). Works best with clients in Retail, Manufacturing, Financial services, Healthcare, Media.
Decision matrix: QuantumBlack, AI by McKinsey vs deepsense.ai
| 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 | QuantumBlack, AI by McKinsey |
| 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 deepsense.ai ($25,000+ (Clutch)) |
| You need a large team across many countries | QuantumBlack, AI by McKinsey |
Use case fit: QuantumBlack, AI by McKinsey vs deepsense.ai
| Use case | QuantumBlack, AI by McKinsey fit | deepsense.ai 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 |
| Workshops to pick a first computer vision or language model project. | Limited | Strong | deepsense.ai |
| Technical feasibility reviews for an AI product idea. | Limited | Strong | deepsense.ai |
Verdict: QuantumBlack, AI by McKinsey vs deepsense.ai
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.
deepsense.ai (3.9/5) is worth a look if you need technical feasibility reviews for an AI product idea. If your situation matches that, deepsense.ai is a competitive option.
Related comparisons
QuantumBlack, AI by McKinsey vs deepsense.ai FAQ
Is QuantumBlack, AI by McKinsey better than deepsense.ai?
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. deepsense.ai's strongest advantage: workshops are run by people who build models, so feasibility advice is concrete.
How do QuantumBlack, AI by McKinsey and deepsense.ai differ in pricing?
QuantumBlack, AI by McKinsey's pricing: project fees set per engagement; rates not published. deepsense.ai's pricing: $100–$149/hr (Clutch band); project-based with a minimum engagement of $25,000+ (Clutch). 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 deepsense.ai?
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 deepsense.ai?
QuantumBlack, AI by McKinsey's primary differentiator is: board-level strategy and change management backed by McKinsey's own AI engineering group. deepsense.ai's primary differentiator is: strategy workshops run by engineers who build vision and language models. They also differ in team size (1,000+ vs 120+), minimum engagement (Not disclosed vs $25,000+ (Clutch)), and primary industries served (Banking & insurance, Healthcare & life sciences vs Retail, Manufacturing).
Verify all details directly with each consultant before making a decision.