At a glance
- Enterprise employees across the board have embraced GenAI.
- Result: Democratization of content creation, with even novice creators generating more and richer files.
- Question: How to seize the value of these tools based on the data they generate?
A new survey from IDC1 shows enterprises have latched on to GenAI. As a result, they’re creating more and richer digital content. Which raises the question: How can enterprises harness the value of newly created data to grow their businesses?
How many enterprises have adopted GenAI? Among those IDC surveyed, all of them. More than half have been using these tools for 12 months or longer.
What are they using it for? These are the top three use cases:
- Creating ad copy, social media posts, customized materials and such for marketing and sales (72%).
- Writing manuals, reports and other business documents (70%).
- Producing concept art, photography, videos, storyboards and other creative assets (58%).
Democratizing creativity. GenAI doesn’t just create content. It also creates content creators.
Three out of four enterprises say that with GenAI, employees in traditional business functions now produce creative content on their own.
For 35% of organizations surveyed, that means less reliance on specialists in graphics and video production.
Do novices pose risks for brand image? IDC says not necessarily. “Creative professionals are not disappearing but evolving, focusing more on oversight, quality assurance, and strategic direction.”
Avalanche of enterprise data. Two-thirds of enterprises say that employees are creating more content files than before they adopted GenAI tools.
It’s not just the quantity of files, but also their size. More than 70% say GenAI is producing bigger files. And 31% say files are now “significantly larger, richer, higher resolution, or more complex.”
Video is a huge factor. “More than 75% of respondents indicate that video file content will increase by at least two times the current amount or more over the next five years due to the use of GenAI.”
What to do with all the iterations? When it’s easy to design a slick brochure, for example, the tendency is to kick one out, vary the prompt and do it again.
The survey bears this out with 57% of enterprises saying they now create “multiple variations of the same content more often.”
For 46%, this results in “saving higher volumes of similar or excess files.”
What happens to these similar or excess files? According to IDC, “25% systematically store all variations, 36% selectively store the best versions, and 25% usually discard extras.”
Storing more, bigger and multiple files. Of the enterprises surveyed, 66% foresee GenAI increasing their volume of stored data over the next two years.
A similar number has upgraded or expanded capacity as a result. That said, only 34% regard their current infrastructure as “fully optimized for GenAI.”
Unlocking value. “The key question is no longer whether data volumes will rise but how enterprises can harness that scale to deliver measurable value,” says the report.
Some output from GenAI is ephemeral. But a great deal offers long-term value — from repurposing in future campaigns and projects to training and fine-tuning AI models.
What to keep and for how long? Only 39% of respondents “have implemented new data governance or content life-cycle policies specifically in response to GenAI adoption.”
Meanwhile, 59% are still working on governance and life-cycle policies — or determining if changes are even necessary. This majority, IDC suggests, is in danger of “being caught off guard.”
Curious about content creation in the age of GenAI? Read more here.
Footnotes
1 IDC White Paper, sponsored by Seagate Technology, Content Creation in the Age of Generative AI: Implications for Value and Scale, US53817625, October 2025
