The Vertical AI Data Bank

80% of organizations still don’t consider AI essential to their workflows 

87% believe their organization risks falling behind, or even becoming obsolete, without successful AI implementation. 

92% say outside expertise or support would help them get more from AI. 

82.5% agree that AI’s value is clear but hasn’t been fully realized yet—expectations are still outpacing outcomes 

40% admit to using AI tools for work without formal approval from their organization—a measure of “shadow AI.” 

88% already allow AI to act autonomously in at least one area, with no human in the loop. 

96% vs. 36% recognize that a formal AI governance framework is required, yet 36% haven’t built one—and 75% call that absence a major barrier to AI success. 

Improvement of 8 of 8 operational metrics were led by organizations using both industry-specific and general purpose AI over those using only general-purpose tools. 

88% say purpose-built, industry-specific AI is critical or very important to them; 99% say it matters at least somewhat. 

77% say general-purpose AI tools are insufficient for the needs of large, complex operations. 

47% cite easier integration with existing systems (such as ERP and supply chain platforms) as one of the main reasons they value purpose-built AI, ahead of more accurate outputs (42%) and stronger ROI (38%). 

98% of organizations are already using or implementing AI—non-adoption is now a statistical rarity. 

86% say operational efficiency has improved over the past year. 

46% say AI is integrated into or essential to their core workflows; the majority (52%) are still progressing from pilots and departmental use toward full integration. 

83% vs. 17% adopted AI driven by opportunity (the chance to move faster and compete harder) rather than fear of falling behind. 

81% say data quality or access is the single greatest barrier to successful AI implementation. 

82% say integrating AI with their core systems is a bigger challenge than the AI itself. 

86% agree that adopting AI without modernizing the systems around it is unlikely to deliver full value. 

43% rank operational efficiency gains as a top-three success metric for AI, followed by cost savings (36%) and decision quality and speed (34%). 

49% allow AI to make autonomous decisions in forecasting and planning, making it the most common area for autonomous AI use, ahead of customer-facing decisions (48%) and strategic decisions (42%). 

77.7% vs. 70.3%  of industry-specific AI users reported a rising net promoter score (NPS), versus general-purpose users; customer retention improved for 84.1% versus 79.7%—both gaps statistically significant. 

57% vs. 38% of North American food and beverage organizations use verticalized AI, versus their Europe (UK/FR/DE/NL) peers. 

48% vs. 31% of North American food and beverage organizations report faster product delivery from AI, versus Europe (UK/FR/DE/NL); revenue growth improved for 45% versus 33%. 

29% vs. 18% of North American apparel organizations say AI is essential to core workflows and decision making, versus Europe (UK/FR/DE/NL). 

50% vs. 41% of North American apparel organizations plan to move at least some of their on-premises enterprise solutions to the cloud in the next 12 months, versus Europe (UK/FR/DE/NL). 

74% vs. 61% of North American transportation and distribution organizations cite regulatory and compliance reassurance as a required safeguard before allowing AI to operate autonomously in higher-risk decisions, versus Europe (UK/FR/DE/NL). 

73% vs. 59% of North American transportation and distribution organizations require ongoing performance monitoring before extending AI autonomy, versus Europe (UK/FR/DE/NL); 65% versus 53% require clear escalation and incident management procedures. 

40% vs. 30% of North American manufacturers report that vertical-specific AI tools exceeded their expectations, versus the manufacturing vertical average. 

49% vs. 34% of Europe (UK/FR/DE/NL) equipment dealers report AI improved compliance and risk management over the past 12 months, versus North America. 

43% vs. 31% of Europe (UK/FR/DE/NL) equipment dealers allow AI to make workforce decisions autonomously, versus North America. 

59% vs. 53% of supply chain leaders in Europe (UK/FR/DE/NL) cite a business case with quantified ROI as most influential for securing AI budget, versus North America; 53% versus 42% cite strategic goal alignment. 

67% of French apparel organizations use AI tools without formal approval—well above the 44% cross-vertical average. 

56% of French equipment dealers use AI tools without formal approval (versus a 45% cross-vertical average), and 55% of those who believe industry specific AI is critical or very important value purpose-built AI for its fit with regulatory and compliance requirements (versus 42% cross-vertical average). 

84% of food and beverage organizations were motivated to adopt AI by opportunity rather than risk.

46% / 45% use verticalized AI / custom-built AI.

23% say AI is essential to core workflows—second only to apparel.

29% vs. 19% of food and beverage vertical-AI users improved forecast accuracy by 10% or more, versus general-purpose AI users.

44% use AI tools without formal approval, above the cross-vertical average.

53% / 55% use verticalized AI / custom-built AI—the highest adoption of any vertical.

24% say AI is essential to core workflows, the highest of any vertical.

46% plan to move at least some on-premises systems to the cloud in the next 12 months (versus a 38% average).

75% / 68% require strong data governance / clear escalation or incident management procedures before granting higher-risk AI autonomy—the most rigorous safeguards of any vertical.

41% report stronger competitive positioning and/or improved workforce morale from AI in the last 12 months, the highest of any vertical.

77% agree AI’s value is clear but hasn’t been realized yet (versus the 82% average).

47% / 37% use verticalized AI / custom-built AI.

47% / 44% report AI delivered faster, more accurate decisions / reduced operating costs.

13% / 12% / 11% improved revenue growth / on-time delivery or order fulfillment rate / customer retention rate by 10% or more over the past year.

64% say operational efficiency and process optimization is where they expect AI to have the greatest impact on their industry over the next 12-18 months(versus a 53% average).

45% / 39% use verticalized AI / custom-built AI—the lowest vertical adoption.

21% strongly agree general-purpose AI is insufficient for large complex operations—below the 32% cross-sector average, the least convinced sector of the need for vertical AI.

46% / 40% allow AI to make autonomous forecasting and planning / customer-facing decisions —below cross-vertical averages, reflecting more caution.

86% agree general-purpose AI is insufficient for large complex operations—the highest of any vertical (versus 77% average).

49% have actually implemented vertical-specific AI.

23% were motivated to adopt AI by perceived risk rather than opportunity (versus 17% cross-vertical)—the most cautious vertical.

27% vs. 18% of equipment-dealer vertical-AI users improved production yield/ waste reduction in the past 12 months, versus general-purpose users; customer retention improved for 23% versus 16%.

22% / 20% / 18% of equipment-dealers report improved operational efficiency / revenue growth / customer retention by 10% or more.

63% currently use general-purpose AI (versus a 72% average)—less reliant on generic tools.

48% / 46% / 45% report AI improved compliance and risk management / decision making / product delivery the most over the past year.

15% / 16% / 14% of supply chain leaders report improved operational efficiency / employee productivity / forecast accuracy by 10% or more.