Managing Technology
How Grassroots Automation Speeds Digital Success
Learn how grassroots automation helps companies speed up digital transformation efforts.
Thomas H. Davenport, Ian Barkin, and Laurianne McLaughlin
Latest Insights from MIT SMR
New Product Development
Driving Manufacturing Efficiency With AI: Pirelli’s Daniele Petecchi
Sam Ransbotham and Shervin Khodabandeh
Key Tech Issues Facing Managers
- Adopting Emerging Technologies
- Managing Technology Risks
- Transforming Your Organization
Technology Innovation Strategy
It’s Time to Take Another Look at Blockchain
Ravi Sarathy, interviewed by Theodore Kinni
Data & Data Culture
Action and Inaction on Data, Analytics, and AI
Thomas H. Davenport and Randy Bean
Technology Implementation
The Business Case for Blockchain in the Enterprise
Ravi Sarathy and Abbie Lundberg
Supply Chains & Logistics
Unlocking the Potential of Digital Twins in Supply Chains
Özden Tozanli and Maria Jesús Saénz
AI & Machine Learning
What Machines Can’t Do (Yet) in Real Work Settings
Thomas H. Davenport and Steven M. Miller
Technology Innovation Strategy
Becoming an ‘AI Powerhouse’ Means Going All In
Thomas H. Davenport and Randy Bean
Key Tech Issues Facing Managers
- Adopting Emerging Technologies
- Managing Technology Risks
- Transforming Your Organization
AI & Machine Learning
Use Open Source for Safer Generative AI Experiments
Aron Culotta and Nicholas Mattei
Financial Management & Risk
Is Your Organization Investing Enough in Responsible AI? ‘Probably Not,’ Says Our Data
David Kiron and Steven Mills
Financial Management & Risk
Risk Intelligence and the Resilient Company
Ananya Sheth and Joseph V. Sinfield
IT Governance & Leadership
Are Responsible AI Programs Ready for Generative AI? Experts Are Doubtful
Elizabeth M. Renieris et al.
IT Governance & Leadership
Responsible AI at Risk: Understanding and Overcoming the Risks of Third-Party AI
Elizabeth M. Renieris et al.
Key Tech Issues Facing Managers
- Adopting Emerging Technologies
- Managing Technology Risks
- Transforming Your Organization
Technology Implementation
Why Manufacturers Need a Phased Approach to Digital Transformation
Nitin Joglekar et al.
Data & Data Culture
Five Key Trends in AI and Data Science for 2024
Thomas H. Davenport and Randy Bean
IT Governance & Leadership
Generative AI at Mastercard: Governance Takes Center Stage
Thomas H. Davenport and Randy Bean
More Insights from MIT SMR
AI & Machine Learning
How to Succeed With Predictive AI
To succeed with machine learning, manage projects as business initiatives, not technology projects.
Eric Siegel and Abbie Lundberg
Technology Implementation
Scaling Automation: Two Proven Paths to Success
Two automation initiatives succeeded by scoring potential processes and combining technical and process knowledge.
Ben Armstrong and Benjamin Berkowitz
Technology Implementation
How Tech Fails Late-Career Workers
Age-related cognitive changes can hinder workers’ technology use, but these strategies can help managers support them.
Stefan Tams
Collaboration
Are Enterprise Social Platforms All Talk?
Knowledge sharing platforms may not deliver full value if users are focused on self-promotion, not learning from others.
Burcu Bulgurcu et al.
Technology Innovation Strategy
Radical Innovation Needs Old-School VC
Innovators working on urgent problems need funders who understand deep-tech opportunities and take a long-term view.
Thomas Ramge and Rafael Laguna de la Vera
Technology Implementation
Why Manufacturers Need a Phased Approach to Digital Transformation
Taking a three-stage approach can increase the likelihood of a successful digital transformation in manufacturing companies.
Nitin Joglekar et al.
AI & Machine Learning
Punk Rock, the Peace Movement, and Open-Source AI: The Mozilla Foundation’s Mark Surman
On the Me, Myself, and AI podcast, Mark Surman discusses Mozilla’s work to protect internet users as AI tools multiply.
Sam Ransbotham and Shervin Khodabandeh
Data & Data Culture
Five Key Trends in AI and Data Science for 2024
Three new surveys of data executives have identified five trends they’ll be paying attention to in 2024.
Thomas H. Davenport and Randy Bean
Sustainability
How Developers Can Lower AI’s Climate Impact
Artificial intelligence developers can make choices that will reduce the emissions generated by AI training models.
Sanjay Podder et al.
AI & Machine Learning
Preparing Your Organization for a Generative Future
This webinar from MIT SMR offers guidance to help business leaders thoughtfully plan a generative AI implementation.