Insights on Artificial Intelligence

From machine learning operations and organizational change to ethical considerations and emerging use cases, this is QuantumBlack, AI by McKinsey’s latest thinking on how organizations can most effectively and responsibly use AI to create business value.

Featured Insights

Digital twins: The foundation of the enterprise metaverse

Companies can leverage digital twins in a way that delivers significant value today—while building the engine for the enterprise metaverse of tomorrow.

Why businesses need explainable AI—and how to deliver it

– As artificial intelligence informs more decisions, companies’ AI systems must be understood by users and those affected by AI use. Actions in two areas can maximize AI’s benefits and minimize risk.

Data ethics: What it means and what it takes

– Every company must establish its own best practices for managing its data. Here are five pitfalls to avoid based on our conversations with experts and early adopters.

Why digital trust truly matters

– Consumer faith in cybersecurity, data privacy, and responsible AI hinges on what companies do today—and establishing this digital trust just might lead to business growth.

Scaling for impact


How to unlock the full value of data? Manage it like a product

– Creating reusable data products and patterns for piecing together data technologies enables companies to derive value from data today and tomorrow.

IoT value set to accelerate through 2030: Where and how to capture it

– New research shows that the Internet of Things offers significant economic value potential, particularly in standardized production settings, but companies must achieve scale to capture it.

Scaling AI like a tech native: The CEO’s role

– Embedding AI across an enterprise to tap its full business value requires shifting from bespoke builds to an industrialized AI factory. MLOps can help, but the CEO must facilitate it.

Winning with AI is a state of mind

– Companies capturing lasting value from artificial intelligence think differently, from the C-suite to the front line. Here’s how to make the shift from opportunistic efforts to a truly AI-enabled organization.

Optimizing data strategy


The data-driven enterprise of 2025

– Rapidly accelerating technology advances, the recognized value of data, and increasing data literacy are changing what it means to be “data driven.”

AI-driven operations forecasting in data-light environments

– Too many companies still rely on manual forecasting because they think AI requires better-quality data than they have available. Nowadays, that’s a costly mistake.

How a tech company went from moving data to using data: An interview with Ericsson’s Sonia Boije

– Ericsson’s head of data enablement explains how the company is enabling its people to make full and effective use of data.

Financial services unchained: The ongoing rise of open financial data

– If open finance continues to accelerate, it could reshape the global financial services ecosystem, change the very idea of banking, and increase pressure on incumbents.

Breaking through data-architecture gridlock to scale AI

– Large-scale data modernization and rapidly evolving data technologies can tie up AI transformations. Five steps give organizations a way to break through the gridlock.

Building trust


Localization of data privacy regulations creates competitive opportunities

– Around the world, new regulations are promoting data localization. To comply, companies must be agile in their investments, but those that get it right could increase their revenues and market share.

Model risk management 2.0 evolves to address continued uncertainty of risk-related events

– Organizations this year plan to enhance their MRM framework capabilities—including risk culture, standards, and procedures—and to upgrade their validation resources with MRM 2.0 firmly on the agenda.

What the draft European Union AI regulations mean for business

– Proposed EU rules are just one more step toward global AI regulation. Here’s how smart organizations are preparing for compliance—and managing AI risk.

Getting to know—and manage—your biggest AI risks

– A systematic approach to identifying and prioritizing AI risks can help organizations effectively target mitigation efforts.

Executive guides


Executive’s guide to developing AI at scale

– Developing artificial intelligence and analytics applications typically involves different processes, technology, and talent than those for traditional software solutions. Executives who possess a solid understanding of the basics can ensure they’re making the right investments in their tech stacks and teams to build reliable solutions at scale. We’ve created an interactive guide to help.

An executive’s guide to AI

– Updated with the latest artificial-intelligence developments, our interactive helps business executives learn the ABCs of AI.

The executive’s AI playbook

– It’s time to break out of pilot purgatory and more effectively apply artificial intelligence and advanced analytics throughout your organization. Our interactive playbook can help.


Insights from our Medium blog by data science professionals, for data science professionals.

Industry perspectives


The Next Normal – The future of biotech: AI-driven drug discovery

– Many diseases today don’t have a cure. One reason is that drug discovery is difficult: finding and developing an effective medicine is a yearslong and very expensive process. But maybe it doesn’t have to be. Experts say AI—if properly integrated into scientists’ research—could revolutionize drug discovery, making it possible for more patients to get the treatments they need.

Vineeta Agarwala on the promise—and limits—of AI in drug discovery

– By helping us learn from every single patient and every piece of data, AI could enable medical breakthroughs, says Andreessen Horowitz general partner Vineeta Agarwala.

‘It will be a paradigm shift’: Daphne Koller on machine learning in drug discovery

– We’re entering a “new era of science”—we finally have enough data and technology to truly enable better drugs for patients, says insitro CEO Daphne Koller.

Smart operators: How leading companies use machine intelligence

– Despite the recent and significant advances in machine intelligence, the full scale of the opportunity is just beginning to unfold. New research reveals why some companies are doing better than others.

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More insights


What matters: How to scale advanced analytics in corporate functions

– Organizations are starting to embrace advanced analytics as a core pillar of innovation within their general and administrative... functions.

How AI can accelerate R&D for cell and gene therapies

– Cell and gene therapies show significant promise but need substantial innovation to unlock full potential for patients. Scaling... digital and analytics in discovery and R&D is part of the solution.

‘We can invent new biology’: Molly Gibson on the power of AI

– The cofounder of Generate Biomedicines, a pioneering new drug development platform, describes how AI and machine learning are... transforming the way we discover new medicines.

Logistics Disruptors: Plus CEO David Liu on why AI should take the wheel in the trucking industry

– David Liu on Plus’s road map to roll out autonomous trucks and the roadblocks that stand in their way.

Author Talks: In defense of big data

– Public discourse is often wary of automation, AI, and data collection, but along with the risks of digital technology comes its... power to address climate change and prevent discrimination.

Smart scheduling: How to solve workforce-planning challenges with AI

– AI-driven schedule optimizers can alleviate age-old scheduling headaches—reducing employee downtime, improving productivity, and... minimizing schedule-related service disruptions.

Tech at the edge: Trends reshaping the future of IT and business

– With technological change accelerating, companies need to make four fundamental shifts.

Building a cybersecurity culture from within: An interview with MongoDB

– MongoDB’s security champions program leadership team discusses how cybersecurity training can create a company-wide culture... that prioritizes security and encourages employees to get involved.

Data ethics: What it means and what it takes

– Every company must establish its own best practices for managing its data. Here are five pitfalls to avoid based on our conversations... with experts and early adopters.

Digital challengers on the next frontier in Central and Eastern Europe

– Our most recent report on economic growth in the CEE region from 2017–21 shows the positive role of digital commerce in... driving value and future growth.

McKinsey Technology Trends Outlook 2022

– Which technology trends matter most for companies in 2022? New analysis by the McKinsey Technology Council highlights the development,... possible uses, and industry effects of advanced technologies.
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