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

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.

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.

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.

Scaling for impact


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.

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.

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.
Executive Briefing

Reimagining your business for AI

– What’s the right approach for getting the most value from artificial intelligence? We find it’s transforming one or two important slices of your business at a time.

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


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.

Generating real-world evidence at scale using advanced analytics

– As pharma companies apply advanced analytics to generate new types of evidence, how do they decide which use cases to target and how to scale them up across the business?

Autonomous supply chain planning for consumer goods companies

– To capitalize on analytics, consumer packaged goods organizations—especially in Asia—can build an integrated system with the power to oversee and control the entire supply chain from end to end.

How AI-driven nudges can transform an operation’s performance

– The right advice at just the right moment can make all the difference to employee satisfaction and performance. New AI-driven approaches are making truly personalized, real-time coaching a reality.

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More insights


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.

Optimizing front- and back-office services in advanced electronics

– By using digital and analytics to simplify end-to-end processes, organizations can improve margins and customer experience.

Using analytics to address inflation risks and strengthen competitive positioning

– In the new inflationary environment, company leaders can protect their business and gain competitive advantage by deploying analytics-aided... strategies.

AI and the super app: An interview with Careem’s Selim Turki

– Careem’s head of data and AI talks about how the Middle Eastern ride-hailing pioneer is using AI technology to simplify... people’s lives.

It’s time to become a digital investing organization

– In the investment sector, AI and other digital technologies are ushering in the next horizon of performance differentiation. Here’s... how to level up.

Quantum computing funding remains strong, but talent gap raises concern

– Our latest Quantum Technology Monitor shows industry interest remains strong, China is upping its game, and talent shortages require... attention.

The next frontier for AI in China could add $600 billion to its economy

– By 2030, AI could disrupt transportation and other key sectors in China, adding significant economic value—but only if strategic... cooperation and capability building occur across multiple dimensions.

Innovation sourcing in biopharma: Four practices to maximize success

– Biopharma companies’ pipelines are full of assets they source externally to access innovation. Four practices will help... ensure their investments flourish at a time of fierce competition.

Pushing granular decisions through analytics

– The potential effect of advanced analytics on grocery retail is great, but retailers will need to seize the opportunity.
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