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The wave of transformation that artificial intelligence tools — large language models and generative AI, in particular — have unleashed feels unprecedented. Unlike previous technological waves, these tools are disrupting even traditional organizational structures, as highlighted in Ethan Mollick’s MIT SMR article “Reinventing the Organization for GenAI and LLMs.”
Leaders are not only exploring how to integrate AI but also grappling with the profound changes it brings to the realms of strategy and innovation, as our most popular artificial intelligence articles of 2024 show.
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This year’s collection of AI must-reads reflects a shared urgency among leaders to unlock AI’s potential while navigating its many challenges. From measuring the business value of AI projects to enhancing KPIs with AI, this collection tackles key problems and offers actionable guidance for organizations striving to stay competitive.
As our featured Me, Myself, and AI podcast episode shows, AI’s capacity to help people tackle complex tasks with fewer resources is reshaping industries. And in a video from the MIT Sloan CIO Symposium, speakers highlight AI threat vectors to watch and the growing complexity of data protection and employee training.
The rapid advancement of generative AI also raises significant ethical, operational, and strategic questions. Who stands to gain the most from AI’s proliferation, and how can organizations balance experimentation with risk management? As research from MIT SMR and its collaborators reveals, responsible AI use requires significant work by leaders.
How can we learn to better live and work alongside AI in 2025? Check out the articles below to get insights from distinguished AI experts.
#1
Reinventing the Organization for GenAI and LLMs
Ethan Mollick
Previous waves of technology have ushered in innovations that strengthened traditional organizational structure. Not so for generative AI and large language models.
#2
What Leaders Should Know About Measuring AI Project Value
Eric Siegel
Most AI/machine learning projects report only on technical metrics that don’t tell leaders how much business value could be delivered. To prevent project failures, press for business metrics instead.
#3
Big Ideas Report: The Future of Strategic Measurement — Enhancing KPIs With AI
Michael Schrage, David Kiron, François Candelon, Shervin Khodabandeh, and Michael Chu
This artificial intelligence and business strategy report looks at how organizations are using AI to evolve their key performance indicators to better align with their strategies and deliver on enterprise goals.
#4
Who Profits the Most From Generative AI?
Kartik Hosanagar and Ramayya Krishnan
Unpacking what it takes to build and deploy a large language model reveals which players stand to gain the most — and where newer entrants might have the best prospects.
#5
Will Large Language Models Really Change How Work Is Done?
Peter Cappelli, Prasanna (Sonny) Tambe, and Valery Yakubovich
Even as organizations adopt increasingly powerful LLMs, they will find it difficult to shed their reliance on humans.
#6
AI and Statistics: Perfect Together
Thomas C. Redman and Roger W. Hoerl
Many companies develop AI models without a solid foundation on which to base predictions — leading to mistrust and failures. Here’s how statistics can help improve results.
#7
When Generative AI Meets Product Development
Tucker J. Marion, Mahdi Srour, and Frank Piller
From ideation to user testing, large language models are allowing companies to explore more ideas and iterate faster.
#8
Bring Your Own AI: How to Balance Risks and Innovation
Nick van der Meulen and Barbara H. Wixom
Banning GenAI tools won’t work. Leaders should set guidelines that let employees experiment: This mitigates risks while opening the door to organizational gains, research shows.
#9
Me, Myself, and AI Podcast: Never Too Much AI — Upwork’s Andrew Rabinovich
Sam Ransbotham and Shervin Khodabandeh
On this episode of the Me, Myself, and AI podcast, Andrew shares his views on the ways AI could take on more complex projects while using fewer resources.
#10
Video: 8 AI Security Issues Leaders Should Watch
MIT Sloan Management Review
In this short video, MIT Sloan CIO Symposium speakers and CIO Leadership Award finalists share advice on the AI threat vectors to focus on now.
Bonus Read
Five Key Trends in AI and Data Science for 2024
Thomas H. Davenport and Randy Bean
In early 2024, Thomas Davenport and Randy Bean wrote that these developing issues should be on every leader’s radar screen. Catch up on their prescient advice.
“The MIT Sloan Management Review is a research-based magazine and digital platform for business executives published at the MIT Sloan School of Management.”
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