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McKinsey Insights & Publications

The case for optimism in uncertain times Targeted and timely: Curating aesthetic care for GLP-1 patients Healthcare revenue cycle management at a strategic turning point: Survey insights How gen AI agents threaten retail banks’ customer relationships The rise of the human–AI workforce Author Talks: What makes teams effective under pressure Scaling mental health where life happens: Helping Santiago thrive across the lifespan An executive’s survival guide to capital projects What it takes to build ‘genius at scale’ Where AI will create value—and where it won’t Can agentic AI (finally) modernize core technologies in insurance? An agile approach to hiring: Mastercard’s tech talent transformation Making mergers work: A playbook for public sector consolidations McKinsey Quantum Technology Monitor 2026: A commercial tipping point Author Talks: A case for gap years and reviving passions that shape us Shopping in the age of AI: Redefining stores for a new era Rigor: What it takes to turn ambition into impact Quantum is almost here: Are you and your systems ready? From promise to impact: How companies can measure—and realize—the full value of AI The deeper forces shaping global trade Transforming from a position of strength: Brambles CEO Graham Chipchase The AI-powered bank: Rewiring for excellence in customer care The future is shared: Financing task-sharing programs in mental health What great leaders know about not knowing it all Beyond the grant: How philanthropy can rewire education financing The robotics tipping point: Physical AI and the race to scale Midmarket insurance: Managing growth in a complex environment Author Talks: The power of human connection How leaders can help their organizations metabolize strain Reinventing marketing workflows with agentic AI
Reimagining tech infrastructure for (and with) agentic AI
2026-04-23 · via McKinsey Insights & Publications
Scaling agentic AI requires turning unstructured data into governed, reusable assets that systems can interpret and trust. Data leaders can start by building shared foundations and enforcing standards.