As part of McKinsey’s ongoing collaboration with Anthropic, a cohort of leading technologists from QuantumBlack, AI by McKinsey, has been selected to join the first Claude Frontier Academy residency program to deepen their expertise in Claude, working directly with Anthropic engineers on Claude deployment, then bring that extended expertise back to lead client work.
This collaboration focuses on leveraging frontier AI to create superior business outcomes for clients. QuantumBlack technologists bring distinctive AI engineering skills, deep domain expertise, and a value creation mindset to client work. The residency will extend that tool kit, giving them enhanced fluency with Claude that they can directly apply to our clients’ most complex enterprise AI challenges.
“The residency puts our best technical talent shoulder to shoulder with the people building and deploying Claude, working the frontier directly,” says McKinsey Senior Partner Dan Tinkoff, global coleader of QuantumBlack, AI by McKinsey. “That’s one of the ways we keep QuantumBlack the place for top applied AI talent at McKinsey.”
Working directly with the most advanced technologies is invaluable for operating at the bleeding edge. Making AI work at scale requires integrating it with existing systems and data, navigating security and governance, and embedding it into business workflows.
“Getting AI into production inside a large enterprise takes people who understand the business as well as frontier technology,” said Steve Corfield, Global Head of Business Development and Partnerships at Anthropic. “McKinsey brings a deep understanding of its clients’ businesses, including the context they operate in and the problems they most need to solve. We’re delighted to have their engineers in the program.”
McKinsey brings a deep understanding of its clients’ businesses, including the context they operate in and the problems they most need to solve. We’re delighted to have their engineers in the program.
For McKinsey’s clients, that expertise translates directly into execution, from connecting models with proprietary data and existing systems to navigating security and governance and redesigning workflows for adoption. By keeping our technical talent close to the frontier, work like this can help close the gap between what the latest AI can do and how organizations can move from AI ambition to scaled impact.