@MIT_CISR

MIT Center for Information Systems Research (CISR), a research center at the MIT Sloan School of Management. Tweets managed by Cheryl Miller

 Cambridge, MA USA
cisr.mit.edu/
Joined May 2010
  • Tweets3.3K
  • Following7.2K
  • Followers9.9K
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High data liquidity (when data assets can easily be reused and combined) boosts business performance, particularly when it comes to AI use. @MIT_CISR mitsloan.mit.edu/ideas-made-…

Data liquidity leads to AI success | MIT Sloan

Three levers — data architecture, data preparation, and data permissions — determine whether data becomes a reusable strategic asset or stays trapped in silos.

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Researchers at @MIT_CISR have demonstrated that companies with high data liquidity outperform their peers on customer experience, speed to market, and data-driven decision-making. mitsloan.mit.edu/ideas-made-…

Data liquidity leads to AI success | MIT Sloan

Three levers — data architecture, data preparation, and data permissions — determine whether data becomes a reusable strategic asset or stays trapped in silos.

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As organizations scale generative AI, traditional governance models prove to be too rigid or too loose. Minimum viable governance puts in place just enough oversight to enable responsible innovation without slowing progress. @MIT_CISR bit.ly/4ewTMDg

Balance AI innovation and risk with ‘minimum viable governance’ | MIT Sloan

As organizations scale generative AI, traditional governance models prove to be too rigid or too loose. Minimum viable governance calibrates oversight to risk, enabling responsible innovation.

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Most organizations struggle to move from AI experimentation to seeing a return on their investments. Here are five common AI mistakes and how you can overcome them. @MIT_CISR bit.ly/4wAhJBB

What leaders still get wrong about AI | MIT Sloan

Organizations are struggling to succeed with AI. Research from the MIT Center for Information Systems Research shows common mistakes and how to overcome them.

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A research brief from @MIT_CISR outlined how business models are evolving to keep pace with advances in AI, and what it takes to successfully navigate change. Learn more: bit.ly/4aUDML5
Graphic titled 'Digital Business Model Shifts 2013 vs. 2025'. Three columns (from left to right) are labeled 'digital business model', 'dominant model in 2013', and 'dominant model in 2025'. The rows of digital business models are 'supplier', 'omnichannel', 'modular producer', and 'ecosystem driver'. Chart shows that the dominant model in 2013 was 'supplier,' at 46% and in 2025, the dominant model was 'ecosystem driver,' at 58%.

ALT Graphic titled 'Digital Business Model Shifts 2013 vs. 2025'. Three columns (from left to right) are labeled 'digital business model', 'dominant model in 2013', and 'dominant model in 2025'. The rows of digital business models are 'supplier', 'omnichannel', 'modular producer', and 'ecosystem driver'. Chart shows that the dominant model in 2013 was 'supplier,' at 46% and in 2025, the dominant model was 'ecosystem driver,' at 58%.

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With the rapid adoption of AI technologies, @MIT_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: bit.ly/4qWCWlH
Graphic titled 'Business Models in the AI Era' that is divided into four quadrants (clockwise from top left): Customer proxy, Orchestrator, Existing+, and Modular curator. The vertical axis, action on behalf of customers, indicates that companies either assist customers (bottom), playing a supportive role in helping them reach outcomes, or represent them (top), autonomously achieving outcomes for them within guardrails. The horizontal axis, business execution, demonstrates companies taking either a structured (left) or adaptive approach (right). The structured approach starts with a specified business process and builds toward outcomes, with AI executing predefined flows of activity.

ALT Graphic titled 'Business Models in the AI Era' that is divided into four quadrants (clockwise from top left): Customer proxy, Orchestrator, Existing+, and Modular curator. The vertical axis, action on behalf of customers, indicates that companies either assist customers (bottom), playing a supportive role in helping them reach outcomes, or represent them (top), autonomously achieving outcomes for them within guardrails. The horizontal axis, business execution, demonstrates companies taking either a structured (left) or adaptive approach (right). The structured approach starts with a specified business process and builds toward outcomes, with AI executing predefined flows of activity.

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Researchers from @MIT_CISR have identified four new business models for the era of agentic artificial intelligence. bit.ly/4aUDML5

How digital business models are evolving in the age of agentic AI | MIT Sloan

As businesses adopt AI, they need to rethink how they make money. Understanding these four new business models is a place to start.

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Researchers from @MIT_CISR have identified four new business models for the era of agentic artificial intelligence. bit.ly/4aUDML5

How digital business models are evolving in the age of agentic AI | MIT Sloan

As businesses adopt AI, they need to rethink how they make money. Understanding these four new business models is a place to start.

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A research brief from @MIT_CISR outlined how business models are evolving to keep pace with advances in AI, and what it takes to successfully navigate change. Learn more: bit.ly/4aUDML5
Graphic titled 'Digital Business Model Shifts, 2013 vs. 2025'. Chart shows four different digital business models and what percentage of the total each made up in 2013 and in 2025. The four models are supplier, omnichannel, modular producer, and ecosystem driver. The dominant model in 2013 was supplier, at 46%, and the dominant model in 2025 was ecosystem driver, at 58%.

ALT Graphic titled 'Digital Business Model Shifts, 2013 vs. 2025'. Chart shows four different digital business models and what percentage of the total each made up in 2013 and in 2025. The four models are supplier, omnichannel, modular producer, and ecosystem driver. The dominant model in 2013 was supplier, at 46%, and the dominant model in 2025 was ecosystem driver, at 58%.

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A recent research brief from @MIT_CISR outlined how business models are evolving to keep pace with advances in AI, and what it takes to successfully navigate change. bit.ly/4aUDML5

How digital business models are evolving in the age of agentic AI | MIT Sloan

As businesses adopt AI, they need to rethink how they make money. Understanding these four new business models is a place to start.

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A data democracy is an organizational state in which employees regularly and universally have access to data assets, along with the skills to exploit them, the motivation to engage with them, and guidance to use them strategically. @MIT_CISR bit.ly/4rsatoN

What is a data democracy, and how can your company build one? | MIT Sloan

Leaders who actively design for the widespread use of data assets generate three times the revenue from data monetization compared with their peers.

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Transitioning through stages of AI maturity represents a major organizational change, and businesses will likely have to overcome both human resistance and technological complexity. @MIT_CISR bit.ly/4nFe3cV

How to boost your organization’s AI maturity level | MIT Sloan

New research highlights four areas leaders must address as they embed AI across their business.

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This research from @NMeulen and @BarbWixom of MIT CISR will help you choose the best path to #GenAI for your org.
MIT Sloan School of Management
@MITSloan17 Sep 2025
Generative artificial intelligence solutions are business-case-driven and address a company’s strategic objectives. Companies have three options for acquiring them. @MIT_CISR bit.ly/4gq1u2h
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“A future-ready company is one that is ambidextrous, that is innovating and pulling out costs at the same time.” — @SL_Woerner, @MIT_CISR bit.ly/4532ghX

How to lead future-ready organizations in times of uncertainty | MIT Sloan

Here are four ways that leaders can effectively respond to challenges and thrive amid the unknown, from MIT Sloan experts.

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Machine learning and generative AI: Which tool should you use — and when? Learn more: bit.ly/4mIQEY2
An educational infographic titled "Which Artificial Intelligence Tool Should You Use – and When?" It discusses the distinctions between generative AI, focusing on language and ideas, and machine learning, which focuses on generalizing patterns. The bottom includes sources credited to Swati Gupta and Rama Ramakrishnan, and the MIT Sloan School of Management logo.

ALT An educational infographic titled "Which Artificial Intelligence Tool Should You Use – and When?" It discusses the distinctions between generative AI, focusing on language and ideas, and machine learning, which focuses on generalizing patterns. The bottom includes sources credited to Swati Gupta and Rama Ramakrishnan, and the MIT Sloan School of Management logo.

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Companies perform better when their boards and executive teams stay current with fast-moving technologies. @MIT_CISR bit.ly/4k2t1rz
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Having a digitally savvy board used to be a competitive differentiator for organizations. Now, it’s corporate boards that are savvy about AI that are helping some companies boost performance, according to @MIT_CISR. Learn more: bit.ly/4k2t1rz
An infographic titled "Board Technology Skills Over Time: Large U.S. Companies," showing increasing focus on digital transformation and cybersecurity from 2019 to 2024+.

ALT An infographic titled "Board Technology Skills Over Time: Large U.S. Companies," showing increasing focus on digital transformation and cybersecurity from 2019 to 2024+.

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MIT CISR retweeted
CIO.com
@CIOonline30 May 2025
Barb Wixom and MIT CISR on managing data like a product cio.com/article/3999313/barb…

Barb Wixom and MIT CISR on managing data like a product

MIT CISR research into information businesses reveals how treating data as a product, complete with owners, lifecycle and metrics, separates leaders from laggards.

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Companies perform better when their boards and executive teams stay current with fast-moving technologies. @MIT_CISR bit.ly/4k2t1rz
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Companies need a plan for when employees use unapproved, publicly accessible generative artificial intelligence tools for work-related tasks. @MIT_CISR bit.ly/3DBtOjj

What leaders should know about ’bring your own AI’ | MIT Sloan

Companies need a plan for when employees use unapproved, publicly accessible generative artificial intelligence tools for work-related tasks.

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