Data, AI, & Machine Learning
Technology Innovation Strategy Becoming an ‘AI Powerhouse’ Means Going All In
Plenty of organizations dabble with AI, but Mastercard’s capabilities — and confidence — set it apart.
Thomas H. Davenport and Randy Bean
Latest Insights from MIT SMR
Technology Innovation Strategy
Transforming Transactions With Technology: eBay’s Nitzan Mekel-Bobrov
Sam Ransbotham and Shervin Khodabandeh
- Technology Ethics
IT Governance & Leadership
Building an Organizational Approach to Responsible AI
Kay Firth-Butterfield
Ethics
Designing Ethical Technology Requires Systems for Anticipation and Resilience
Kirsten Martin and Bidhan (Bobby) L. Parmar
Ethics
Why Building an Ethical Culture Must Start at the Top
Robert Chesnut, interviewed by Ally MacDonald
- Leading Data & Analytics
- Data Strategy
- Technology Ethics
- Leading Data & Analytics
Data & Data Culture
Empowering a Data Culture From the Inside Out
Jonathan Tudor, interviewed by Ally MacDonald
Analytics & Business Intelligence
Leading With Decision-Driven Data Analytics
Bart de Langhe and Stefano Puntoni
- Data Strategy
- Technology Ethics
- Leading Data & Analytics
- Data Strategy
IT Governance & Leadership
The Enterprise Systems That Companies Need to Create
David Waller and Paul Beswick
Analytics & Business Intelligence
Actioned Analytics Pave the Way to New Customer Value
Barbara H. Wixom and Gabriele Piccoli
Analytics & Business Intelligence
Getting Serious About Data and Data Science
Thomas C. Redman and Thomas H. Davenport
More Insights from MIT SMR
AI & Machine Learning
AI on the Front Lines
Successful AI adoption requires developers to think beyond business goals and address end users’ workflow concerns.
Katherine C. Kellogg et al.
Data & Data Culture
The Collaboration Muscle: LinkedIn’s Ya Xu
LinkedIn’s Ya Xu discusses leading the high-traffic site’s team of data scientists and delivering value to consumers.
Sam Ransbotham and Shervin Khodabandeh
Talent Management
Imagining Work Without Jobs
To gain agility, leaders must deconstruct jobs into tasks and deploy workers based on their skills.
Ravin Jesuthasan et al.
Security & Privacy
Preserving Privacy While Sharing Data
Using differential privacy to safeguard personal information when sharing data still requires a high level of expertise.
Simson L. Garfinkel and Claire McKay Bowen
Boards & Corporate Governance
Why Top Management Should Focus on Responsible AI
A panel of AI experts weighs in on whether responsible AI should be at the top of leaders’ management agendas.
David Kiron et al.
Data & Data Culture
Turning Sound Into Information: Warner Music Group’s Kobi Abayomi
Warner Music Group’s Kobi Abayomi shares how AI helps customers discover new music, and his approach to hiring data scientists.
Sam Ransbotham and Shervin Khodabandeh
Data & Data Culture
Framing Data Science Problems the Right Way From the Start
Data science project failure can often be attributed to poor problem definition, but early intervention can prevent it.
Roger Hoerl et al.
AI & Machine Learning
Clinical AI Gets the Headlines, but Administrative AI May Be a Better Bet
Health care organizations are seeing significant savings using AI in administrative systems.
Thomas H. Davenport and Randy Bean
Skills & Learning
From Journalism to Jeans: Levi Strauss & Co.’s Katia Walsh
Katia Walsh discusses how Levi Strauss is upskilling and motivating employees to help drive its digital transformation.
Sam Ransbotham and Shervin Khodabandeh
Customers
How Do Customers React When Their Requests Are Evaluated by Algorithms?
Managers’ intuition about how customers will feel about decisions made by algorithms rather than humans is often wrong.