MIT Center for Information Systems Research - CISR

A research brief from MIT CISR (MIT Center for Information Systems Research) outlined how digital business models are evolving to keep pace with advances in AI, and what it takes to successfully navigate change.

Learn more: https://bit.ly/4qQ0Ij5

With the rapid adoption of AI technologies — including machine learning and generative, agentic, and robotic AI — the MIT Center for Information Systems Research - CISR created a business model framework for the AI era that shows businesses evolving to become increasingly outcome oriented and enabled by autonomous AI.

Learn more: https://bit.ly/4qQ0Ij5

Having a digitally savvy board used to be a competitive differentiator for organizations — but today it’s merely table stakes. Now, it’s corporate boards that are savvy about AI that are helping some companies outperform others, according to MIT CISR (MIT Center for Information Systems Research).

Learn more: https://bit.ly/43gxlME

Unlocking the Power of Data Monetization and AI-Driven Business Transformation - CXO Outlook Dr. Barbara Wixom is a Principal Research Scientist at the MIT Sloan School of Management’s Center for Information Systems Research (CISR), where she explores how organizations generate value from data assets. Since 1994, Dr. Wixom has been a leading academic voice in data analytics, with research...

Barb Wixom talks about Monetizing Data With AI in today's episode of the Me, Myself, and AI podcast from MIT Sloan Management Review.

https://sloanreview.mit.edu/audio/monetizing-data-with-ai-mit-cisrs-barb-wixom/

Participate in MIT CISR Research

Take Our New Survey on Real-Time Businesses
The next competitive step for many companies will be to become a real-time business (RTB). An RTB executes its key business processes in real-time, using automated digitized operations, AI, and data-driven decisions made by employees, supported by governance and risk guardrails. By completing this survey, you are helping us identify best practices as companies become real-time businesses.

The right person to answer this survey is familiar with the digital strategy of the enterprise. It will take 20–25 minutes to complete the survey. Click the link here to respond!
https://survey.qualtrics.com/jfe/form/SV_6sRpiaTpZGnZCjY

Bring Your Own AI: Balance Rewards and Risks
Free Webinar and Q&A from MIT Sloan Management Review
Thursday January 30, 2025, at 11 am EST

With the rise of comes a new challenge for leaders: how to manage the phenomenon of Bring Your Own (BYOAI). Employees using unvetted, publicly available GenAI tools—like and —open the door for risk. But banning tools, while tempting, won’t work. New research from Nick van der Meulen and Barbara Wixom of MIT CISR points to how leaders can turn these BYOAI tools from a liability to an asset that drives innovation.

In this webinar you will learn:
• Why BYOAI tools come with both risk and reward
• Three key steps to crafting a smart BYOAI strategy, including setting up a cross-functional leadership team, training, and communities of practice
• How to make the case for sanctioning a limited number of BYOAI tools.



REGISTER NOW! https://mitsmr.com/401DfAU

New research found that companies can achieve value from sustainability by embedding sustainability goals into company strategy and then developing capabilities to advance these goals. In MIT CISR's January 2025 briefing, authors Ina Sebastian, Stephanie Woerner, Peter Weill, and Daniel Woerner identify four distinct sustainability goals.

Business Value from Digital Sustainability Sustainability is a cost of doing business for many companies today—but it is also an opportunity for creating value. Companies only achieve value, however, by embedding sustainability goals into company strategy and then developing capabilities to advance these goals. Our survey analysis suggeste...

New MIT CISR research identified four stages of enterprise AI maturity, and found that financial performance improves with each stage. Most enterprises in the research were in the first two stages of AI maturity and had financial performance below industry average, while enterprises in stages three and four had financial performance well above industry average.

MIT CISR researchers Peter Weill, Stephanie Woerner, and Ina Sebastian detail these findings in CISR's December 2024 research briefing, titled “Building Enterprise AI Maturity,” and explain how enterprises need to cumulatively build capabilities and learnings from AI as they move toward a future-ready state of AI use. The briefing also describes what enterprises focus on in each of the four stages, and pinpoints capabilities an enterprise needs as it progresses through the stages.

Building Enterprise AI Maturity With so much excitement and hype around AI, we pursued research that would help leaders make sense of the chaos and understand how enterprises create value with AI. This briefing describes the MIT CISR Enterprise AI Maturity model, which depicts four stages of enterprise AI maturity we identified ba...

Organizations are distinguishing between two types of generative AI implementations: broadly applicable tools that boost personal productivity, and tailored solutions for specific purposes. Research from Nick van der Meulen and Barb Wixom identified challenges of each type and strategies to address them, as described in this article in Ideas Made to Matter from the MIT Sloan School of Management.

How to manage two types of generative artificial intelligence | MIT Sloan Through intellectual rigor and experiential learning, this full-time, two-year MBA program develops leaders who make a difference in the world.

Top-performing organizations in MIT CISR research attributed more than 5 times the revenues to data monetization compared to bottom-performing organizations. Barb Wixom, Cynthia Beath, and Ja-Nae Duane describe 3 high-performance factors that amplify data monetization impact, and illustrate them with a case study of Wolters Kluwer, in our November '24 research briefing.

High-Performance Data Monetization Top-performing organizations invest in three factors that amplify the financial impact of data monetization: CEO-level data leadership, data value management, and data lifecycle measurement. These high-performance factors establish an organizational culture conducive to maximized data monetization.....