Tackling the Hard Part on Enterprise AI

Coming up with usable AI-powered tools isn’t the hard part – making the business case for spending on AI within the enterprise is.

3 Min Read
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This article originally appeared on No Jitter.

A few weeks back, I wrote about the new kinds of shadow IT challenges we’re likely to see in the era of Generative AI, and it looks like those challenges are already upon us. In their latest Work Trend Index, released this week, Microsoft and LinkedIn even coin the acronym BYOAI, and report that around 80% of those who use AI at work are bringing their own.

The survey offers evidence that this BYO trend ties directly to the AI boom ignited in late 2022 with the introduction of ChatGPT, and the subsequent barrage of coverage, commentary, and general zeitgeist-domination that followed. Of the 75% of people that already use AI at work, 46% started using it less than six months ago, according to the report.

This may motivate some enterprises to bolster their policies and plans around AI, but it doesn’t necessarily lead them any closer to a positive business case for AI in their enterprise, which is evident from the report’s title: “AI at Work Is Here. Now Comes the Hard Part.”

The hard part, as the survey makes clear, is cost-justifying the AI investment. According to the report:

While most leaders agree AI is a necessity, the pressure to show immediate ROI is making leaders move slowly.

  • 79% of leaders agree their company needs to adopt AI to stay competitive, but 59% worry about quantifying the productivity gains of AI.

  • This uncertainty is stalling vision. 60% of leaders worry their organization’s leadership lacks a plan and vision to implement AI.

Related:AI Use in Cyberattacks Raises Worker Cybersecurity Concerns

Given how much Microsoft has staked on AI, it’s noteworthy that they call out this lack of vision and strategy near the top of the report. The company certainly doesn’t lack confidence in its AI offerings, but seems to be acknowledging that many enterprises have yet to fully buy into the vision or find a way it pays off for them.

I’ve heard this sentiment from a number of enterprise folks at and since Enterprise Connect 2024 in March, and it’s one of the reasons we’re launching Enterprise Connect AI in Santa Clara, CA, Oct. 1 – 2. We’ll be starting to post elements of the program this month, and there will be a heavy focus on sessions that help enterprises find the value that AI, and specifically Gen AI, offers their business. We’re going to be looking for use cases and implementation advice that aims to help enterprise leaders choose the right course for their use of AI. If you have one of these use cases, or other valuable, practical insights about implementing AI in the enterprise, I’d encourage you to submit a proposal to our Call for Speakers, which closes next week, May 17.

And of course we hope you’ll join us in Santa Clara this fall and be part of the AI transformation. You can’t afford to ignore AI, but you’ve also got to get it right. The hard part is here; we aim to make it a little easier for you.

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No Jitter

About the Author(s)

Eric Krapf

Eric Krapf is general manager and program co-chair for Enterprise Connect, the leading conference/exhibition and online events brand in the enterprise communications industry. He has been Enterprise Connect's program co-chair for over a decade. He is also publisher of No Jitter, the Enterprise Connect community's daily news and analysis website.

Eric served as editor of No Jitter from its founding in 2007 until taking over as publisher in 2015. From 1996 to 2004, Eric was managing editor of Business Communications Review (BCR) magazine, and from 2004 to 2007, he was the magazine's editor. BCR was a highly respected journal of the business technology and communications industry.

Before joining BCR, he was managing editor and senior editor of America's Network magazine, covering the public telecommunications industry. Prior to working in high-tech journalism, he was a reporter and editor at newspapers in Connecticut and Texas.

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