From Gartner’s sobering enterprise data statistics to the podcast automation trap. How to fund training like a launch and data like a utility.
EXPERT OPINION BY PAM DIDNER, B2B MARKETING CONSULTANT AND AI STRATEGIST
The more I work with AI, the less I worry about AI—I worry about the data. If your data quality isn’t there, the quality of the AI’s output isn’t there, either. You can’t put lipstick on a pig, so you need to start with optimizing your AI strategy.
My team and I learned this while building a podcast outreach automation, and I see the same pattern with clients. Every leader eventually faces the same question: with a finite budget, does the next AI dollar go to your people or to your data?
Busy teams won’t teach themselves AI
Customized training is the fastest way to get a team using AI, because busy professionals don’t have time to teach themselves. They have full-time jobs. They can barely finish their daily deliverables, and that’s before the back-to-back meetings.
The research backs this up. A Workera survey of 1,000 U.S. enterprise employees, published in September 2026, found that 56 percent cite no time set aside during work hours as a barrier to building AI skills. BCG’s AI at Work 2025 survey found that only 36 percent of employees feel adequately trained, and that people who get five or more hours of training, especially in person with coaching, are significantly more likely to become regular users.
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That’s why many enterprise marketing and sales teams bring in a trainer and build sessions around their own use cases and workflows. In the customized sessions I’ve run, active AI usage 30 days after training was up by more than 70 percent. Show employees the ropes using their own work, and they run with it.
Customized training is the investment people can see.
Good data is the investment nobody sees
People are visible. Data is invisible, and what we don’t see, we don’t fund. As simple as that.
Source: www.inc.com
