MIT’s new CISR study provides insight into how to invest in capabilities, engage work staff, and realize value from both predictive and generative AI.
AI is everyone’s business
CAMBRIDGE, Mass., May 16, 2024 (Globe Newswire) — A new research brief released today by the MIT Center for Information Systems Research (CISR) guides business leaders as they develop artificial intelligence (AI). Three principles have been established that are supported by data monetization research. )investment.
This research brief, titled “AI is Everyone’s Business,” explores managing AI using the idea of data monetization and was written by Barbara H. Wixom and Cynthia M. Bies, authors of the award-winning book Written by. Data is everyone’s business: The basics of data monetization. Wixom is a principal investigator at MIT CISR, and Bears is a professor emeritus at the University of Texas and an academic fellow at MIT CISR.
“In our data monetization research, we regularly see leaders effectively leveraging AI to realize extraordinary business objectives,” said Wixom. “The role of AI technology is to enable data monetization project teams to use data in ways that are typically not possible due to the complexity, scope, and speed required.”
Principle 1: Invest in practices that build the capabilities needed for AI
According to MIT CISR research, an organization’s AI advancements depend on having similarly advanced capabilities in data science, data management, data platforms, acceptable data use, and customer understanding.
The authors argue that while investing in AI training is important, investing in practices that increase an organization’s data management capabilities (such as implementing data cataloging tools) and making data cost-effective (such as cloud deployments) is important. We emphasize that it is equally important to: policy), improve data governance (e.g. establishing an ethics oversight board), and strengthen customer understanding (e.g. customer journey mapping).
In particular, adopting policies and processes that improve an organization’s data governance ensures that data is only used for AI initiatives in ways that align with its values and regulatory environment.
“We are concerned that some leaders see purchasing AI products from providers as an opportunity to use AI without deep scientific skills. I don’t recommend it,” Beas warned.
Principle 2: Involve the entire organization in AI efforts
AI involves involving a variety of stakeholders in initiatives so that people other than data scientists can understand what AI can and cannot do, and how long it will take to deliver certain types of functionality. , gain knowledge about the cost of AI solutions. This also helps organizations learn how to build models that people trust.
Given the consumerization of generative AI tools, MIT’s CISR study found that extensive employee involvement in ideating, building, refining, using, and testing AI models and tools will lead to the development of fruitful AI projects and the This has been shown to be even more important in building trust that they will perform. Do the right thing at the right time and in the right way.
Principle 3: Focus on realizing value from AI projects
AI is expensive, and some organizations are distracted by endless experiments when they need to make the most of it. Leaders with data monetization experience help ensure that AI projects deliver value in the form of increased revenue or reduced expenses by supporting efforts that are clearly aligned with real-world challenges and opportunities.
According to research from MIT CISR, leaders who see value from data monetization efforts measure and track their results, especially financial results, and hold someone accountable for achieving the desired financial returns. I realized that I was inflicting it.
“When people are proactive about data monetization efforts, Utilizing AI They learn and in turn help the organization learn,” Wixom said. “Their involvement means that people involvement leads to better data and more end value, which leads to new ideas and more engagement, which further improves data and delivers more value.” It creates momentum that starts a virtuous cycle.”
“Imagine this happening across your organization, as everyone in the world is in the business of finding ways to monetize data using AI. That’s why it’s everyone’s business as well,” Beath concluded.
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CONTACT: Casey Bayer MIT Sloan School of Management 914.584.9095 bayerc@mit.edu Patricia Favreau MIT Sloan School of Management 617.895.6025 pfavreau@mit.edu
