Survey: AI Strategies, Management Models Are Still Immature

A new Endeavor Business Intelligence report shows that there’s little consensus on who should lead AI strategy and how it should be funded. Is there an opening to take more time to refine your approach?
March 26, 2026
4 min read

Key Highlights

  • Most organizations lack a clear AI leadership blueprint, with only 20% of survey respondent citing the C-suite as responsible for AI strategy.
  • Talent shortages and unclear business cases are the top barriers to deeper AI adoption, requiring strategic investment and planning.
  • Long-term AI success may be increasingly dependent on technology maturity and cross-departmental integration.
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A new survey of more than 260 business leaders in over a dozen industries presents a clear takeaway for executive teams who feel like they haven’t quite figured out how to make artificial intelligence work for them: You have more time than you think.

In early- and mid-February, Endeavor Business Intelligence, the research arm of ExecutiveEDGE parent company EndeavorB2B, polled a broad sample of professionals about their organizations’ AI strategies and investments. What emerged was a patchwork of approaches — in some cases, merely the beginnings of approaches — and attitudes about how businesses are putting AI into broad practice.

Among the notable data points that emerged from EBI’s research are that:

  • No management/ownership blueprint is dominant – On who should be primarily responsible for driving AI strategy, respondents’ most popular response was the C-suite — but that answer received only 20% of votes. A dedicated AI leader or team came in right behind, while 28% of people said their organization hasn’t yet decided just who ought to be leading the charge.
  • Dedicated AI budgets are in the minority – Nearly half of respondents said their organizations don’t have and aren’t planning to have a specific pot of money to fund AI initiatives. On the flip side, only 10% have dedicated budgets for both AI technology and talent.
  • The barriers to truly moving forward are daunting – Asked about the biggest obstacles to deeper AI adoption, 23% of respondents pointed to a lack of talent and expertise, while 22% cited the absence of a clear business case. Overcoming those hurdles isn’t a quick fix at most organizations.

EBI’s findings suggest that most businesses will — even if small, localized projects produce quick and/or sizable wins — take a while to generate real returns from their AI work. In a recent piece for EndeavorB2B’s Foundry Management & Technology brand, Gustavo Milan and Daniel Krampe of SAP wrote that having the technology mature in many parts of a business will be key to long-term AI successes.

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“The interaction of generative AI, agentic AI and machine learning across different areas of an organization holds the greatest promise in solving long-term labor shortages,” the SAP team wrote. “AI can already let a customer snap a photo of a damaged part and identify it for replacement. Its real power will manifest when AI can also determine the part’s inventory status and locations, establish shipping terms and timing, add the part to the procurement queue to replenish once it’s sold, alert engineering that a design change for a chronic defect may be in order and propose alternative designs.”

Emerson Electric Co. is pushing toward such a cross-departmental approach. Speaking at the recent JPMorgan Industrials Conference, COO Ram Krishnan said he’s focused for now on Emerson’s finance and customer care teams, which combined are home to about 10,000 people around the world. Krishnan said there are opportunities to put agentic AI systems on top of Emerson’s Oracle, Salesforce and other platforms housing customer service, financial planning and receivables information, among others.

Still, Krishnan said Emerson’s work will take time to deliver savings. Some will start to show themselves next year, he said, before adding up to productivity gains of 30% by 2029 versus today’s baseline.

“We’re making meaningful investments in frontier models. Now it will obviously [be] in partnership with hyperscalers and open-source technology,” Krishnan said. “It’s early but we do believe that there are 30% productivity opportunities if those solutions work.”

Savings of about 30% in part of your back-office operations by 2029? Putting the promise of AI that way doesn’t sound as daunting or as urgent as the stories of massive payoffs that are surfacing these days from firms eager to make a splash. Yes, it’s time to get to work and solidify your vision and plans. But being thorough and ambitious rather than rushed and myopic is starting to look like the better path.

To download the “AI Integration Index” report, visit the EBI blog right here.

About the Author

Geert De Lombaerde

Geert De Lombaerde

Contributor

A native of Belgium, Geert De Lombaerde joined EndeavorB2B in September 2021 to cover public companies, markets, and economic trends primarily for IndustryWeek, FleetOwner, Oil & Gas Journal, T&D World, and Healthcare Innovation. His work focuses on strategy, leadership, capital spending, and mergers and acquisitions, and he also works with Endeavor Business Intelligence on surveys and data projects.

Geert has been in business journalism since the mid-1990s. With a degree in journalism from the University of Missouri, he began his reporting career at the Business Courier in Cincinnati, initially covering retail and the courts before shifting to banking, insurance, and investing. He later was managing editor and editor of the Nashville Business Journal before being named editor of the Nashville Post in 2008. He led a team that helped grow the Post's online traffic by an average of more than 15% annually before joining Endeavor.

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