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Data quality: Editorially Reviewed
Language (LLM / NLP)
Custom model development
Telecommunications
Data engineering & preparation
AI strategy & roadmap consulting
Workflow orchestration
Implementation & integration
Analytics & decision support
Predictive / classical ML
Demand planning
Healthcare & life sciences
Pharmaceuticals
ML lifecycle & data
Change management & adoption
Manufacturing
AI strategy & leadership
Data strategy & engineering
Cross-industry / Horizontal
AI Strategy Advisory
Agentic / autonomous
Enterprise
Optimization & decision intelligence
Customer support automation

QuantumBlack, AI by McKinsey

AI strategy & roadmap consulting

Offered by McKinsey & Company

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Overview

QuantumBlack, AI by McKinsey, is the firm's AI and engineering center of excellence, joining McKinsey in 2015 after starting in London. It spans more than 40 offices and offers AI scaling, data transformation, digital twins and AI for social impact, blending data science, engineering, product and design. It builds AI agents for supply chain, software development, customer service and finance operations, and maintains open-source tools including Kedro, CausalNex and Vizro. Case studies reference life sciences, pharmaceuticals, retail, telecommunications and manufacturing, with NVIDIA named as a partner.

Pricing model
On request
Regions served
Global
Categories
Language (LLM / NLP), Custom model development, Telecommunications, Data engineering & preparation, AI strategy & roadmap consulting, Workflow orchestration, Implementation & integration, Analytics & decision support, Predictive / classical ML, Demand planning, Healthcare & life sciences, Pharmaceuticals, ML lifecycle & data, Change management & adoption, Manufacturing, AI strategy & leadership, Data strategy & engineering, Cross-industry / Horizontal, AI Strategy Advisory, Agentic / autonomous, Enterprise, Optimization & decision intelligence, Customer support automation
Last updated
7 October 2026
Published
7 October 2026

Use cases

ML lifecycle & data
Workflow orchestration
Customer support automation
Analytics & decision support
Demand planning

Data sources & provenance

Where this information came from, how it was checked and when it was last looked at. “Last updated” records a change to the record — it does not mean the record was verified.

Data quality
Data quality: Editorially Reviewed
Primary source
mckinsey.com
Sources cited
2
Last reviewed
6 October 2026
Last updated
7 October 2026

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