The promise of AI is undeniable, but transforming organizations to fully embrace it is no small feat. Our survey of over 3,000 business managers across the United States, conducted by Snowfire, dives into the question: “In your view, what is the most significant barrier to AI transformation in your organization?” The answers reveal a complex landscape of challenges, shaped by regional economies, workforce dynamics, and organizational priorities.
Nationwide, 26% of managers identify a skills gap or lack of talent as the top barrier to AI transformation. States like South Dakota (43%), North Dakota (38%), and Illinois (36%) report acute shortages, particularly in industries like agriculture and manufacturing, where AI expertise is still scarce.
Cultural resistance to change, cited by 23% of managers, is a close second. States like Hawaii (50%), Maine (36%), and Montana (36%) highlight reluctance to adopt AI, often in traditional sectors like tourism and forestry, where established practices dominate.
Budget limitations are a concern for 22% of businesses, with states like Wyoming (67%), Vermont (40%), and New Mexico (38%) feeling the pinch. Smaller economies and rural regions struggle to allocate funds for AI infrastructure amidst competing priorities.
Lack of strategic alignment (15%) and unclear ROI (14%) round out the barriers. Rhode Island (33% strategic alignment) and New Hampshire (45% unclear ROI) stand out, reflecting challenges in aligning AI with business goals or quantifying its value in early adoption stages.
Barriers vary by region. Tech hubs like California (25% skills gap) and New York (30% skills gap) face talent shortages due to high demand, while rural states like Arkansas (33% unclear ROI) and Iowa (30% cultural resistance) grapple with uncertainty and traditional mindsets. These differences underscore the need for tailored solutions.
AI transformation is a journey fraught with obstacles, from talent shortages in South Dakota to budget constraints in Wyoming. Yet, these barriers also point to opportunities—investing in training, fostering cultural change, and clarifying ROI can unlock AI’s potential. As businesses navigate this landscape, addressing these challenges head-on will define the next era of innovation.
Online panel survey of 3,003 business managers based on age, gender, and geography. Internal data sources ensure representative population data through stratified sampling and post-stratification weighting. Respondents are selected from a geographically diverse, double-opt-in online panel, with questions designed to authenticate participants. Data quality is maintained through digital fingerprinting, bot checks, geo-verification, speeding detection, and thorough response reviews, including scrutiny of open-ended answers for accuracy and originality.
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