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Businesses have identified two types of generative AI: broadly applicable tools that boost personal productivity, and tailored solutions for specific purposes.
Copyright: mitsloan.mit.edu – “How to Manage Two Types of Generative Artificial Intelligence”
According to a new research briefing by researchers Nick van der Meulen and Barbara H. Wixom at the MIT Center for Information Systems Research, organizations are distinguishing between two types of generative AI implementations. The first, broadly applicable generative AI tools, are used to boost personal productivity. The second, tailored generative AI solutions, are designed for use by specific groups of organizational stakeholders.
The research, which is based on roundtable discussions with members of the MIT CISR Data Research Advisory Board and interviews with executives, outlines the two approaches and highlights unique challenges and management principles for both.
Broadly applicable generative AI tools
Generative AI tools like conversational AI systems and digital assistants embedded in productivity software are broadly applicable by design. They are versatile, and their use is typically defined and refined by its users, the researchers write.
“This is AI for everyone,” said J.D. Williams, a vice president and chief data and analytics officer at global animal health company Zoetis, which is a member of the MIT CISR data board. “It’s where you’re bringing in external products and privatizing them within the company so your data is protected.”
Generative AI tools pose four key challenges to organizations, according to the researchers:
- Because generative AI tools are based on large language models trained to predict the most likely sequence of words in a given context, they often produce output that is common. As a result, the quality and relevance of the output depends on the specificity of the prompts a user enters.[…]
Read more: www.mitsloan.mit.edu
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