Greater clarity and more information about the data used in A.I. models, executives say, will bolster corporate confidence in the technology. How widely the proposed standards will be used is uncertain, and much will depend on how easy the standards are to apply and automate. But standards have accelerated the use of every significant technology, from electricity to the internet.

“This is a step toward managing data as an asset, which is what everyone in industry is trying to do today,” said Ken Finnerty, president for information technology and data analytics at UPS. “To do that, you have to know where the data was created, under what circumstances, its intended purpose and where it’s legal to use or not.”

Surveys point to the need for greater confidence in data and for improved efficiency in data handling. In one poll of corporate chief executives, a majority cited “concerns about data lineage or provenance” as a key barrier to A.I. adoption. And a survey of data scientists found that they spent nearly 40 percent of their time on data preparation tasks.

The data initiative is mainly intended for business data that companies use to make their own A.I. programs or data they may selectively feed into A.I. systems from companies like Google, OpenAI, Microsoft and Anthropic. The more accurate and trustworthy the data, the more reliable the A.I.-generated answers.

For years, companies have been using A.I. in applications that range from tailoring product recommendations to predicting when jet engines will need maintenance.