AI Adoption Rate by Industry

Report highlights. According to the latest available data, nearly three quarters of businesses use AI in at least one part of their business.

• 72% of companies use AI to at least some degree. 
• Information technology shows the highest use of AI (18.1%).
• Construction and agriculture are tied for the lowest use of AI (1.4%).
• Large (7.2%) and small companies (5.5%) use AI at higher rates than medium-sized companies (<5%).
• Nearly two-thirds (65%) of organizations now regularly use generative AI. 
• Despite growth, 74% of companies who have adopted AI report struggling to reap its full benefits. 
• 34% of businesses report using AI for marketing and sales.
• Of organizations using AI, 44% use it for research and development while 39% apply AI to reskilling and workforce development.

AI adoption in higher education

AI adoption in higher education is growing and is a strategic priority for more than half of institutions, specifically 57%.

• 57% of institutions name AI a strategic priority in 2025, up from 49% last year. 
• 39% of institutions report having an AI-related acceptable-use policy (AUP) in 2025, increasing from 23% last year. 
• Academic integrity (74%), coursework (65%), assessment practices (54%), and curriculum design (54%) are the top areas where AI is being used in higher education.
• A Forbes analysis reveals that Massachusetts Institute of Technology (MIT), Harvard, and Princeton Universities each report about an 11% rate of adoption of AI. Others, such as Stanford, Carnegie Mellon, and Columbia, stand at about 6%. 
• Teacher AI adoption rates (66%) nearly match those of student AI adoption (67%) at both the college and high school levels.
• The primary benefit of AI reported by professors is accelerated concept learning among students (49%).

AI adoption in manufacturing

AI adoption in manufacturing continues to accelerate, with most firms implementing solutions across production, inventory management, and customer service.

• A 2025 Rootstock survey states that 77% of manufacturers adopted AI in 2024, up from 70% in 2023.
• Manufacturers use AI mostly for production (31%), followed by inventory management (28%), customer service (28%), and employee training (25%). 
• 83% of manufacturing business leaders believe AI has had a positive impact or will do so in the future.
• 93% of manufacturers see AI as key to growth and innovation. 
• 75% of companies apply AI to optimize production, costs, inventory, and quality control, while 63% use it to predict sales, prices, and maintenance needs). 
• 53% of manufacturers prefer collaborative AI solutions over fully automated AI agents (22%). 
• Nearly half (49%) of manufacturers report efficiency as the top benefit of AI adoption, whereas only 40% see it improving productivity. 

Types of AI used by manufacturers

The types of AI used by manufacturers include automation, IoT systems, generative AI, and predictive AI.

• 57% of manufacturers used AI automation software to simplify workflows, handle administrative tasks, and decrease manual labor requirements.
• 51% of organizations used AI-powered Internet of Things (IoT) systems that monitor manufacturing processes, allow real-time data collection, and reduce manual intervention.
• 50% of manufacturers leverage generative AI for content creation, simulations, and innovative problem-solving methods.
• Predictive AI was used by 42% of manufacturers to forecast equipment maintenance needs, production requirements, and more.

Top drivers

The top drivers of AI adoption in manufacturing are supply chain management, big data/analytics, and consumer relations.

• 49% of manufacturers find supply chain management to be the primary reason to adopt AI.
• Almost half (43%) of manufacturers cite big data/analytics as motivation for adopting AI.
• Customer relationship management (34%), product lifecycle management (33%), and enterprise resource management (32%) are also reasons manufacturers are adopting AI.

Top barriers

The top barriers to manufacturing AI adoption include knowledge gaps, integration challenges, and concerns about implementation costs and ROI.

• Manufacturers report a lack of internal expertise or knowledge (45%) and integration challenges (44%) as main obstacles to AI adoption.
• Additional obstacles include high implementation costs (37%), uncertain ROI (24%), and leadership or stakeholder resistance (21%).

AI adoption in healthcare

AI adoption in healthcare has grown to nearly three-quarters of organizations embracing AI solutions.

• 70% of healthcare organizations have already implemented generative AI or are actively pursuing proofs of concept.
• Only 11% of healthcare organizations have no current plans to adopt AI.
• 59% of those that have implemented generative AI have customized third-party systems, while 24% built in-house solutions, and 17% purchased standardized systems.
• 60% of healthcare organizations using generative AI either expect to see a positive impact from its use or have already.
• 73% of organizations identify clinical productivity as the primary benefit of generative AI, followed by patient engagement (62%) and administrative efficiency (60%).
• Quality of care (48%) and IT infrastructure (42%) are perceived as other generative AI benefits.
• 60% of healthcare organizations reported risk concerns as the biggest barrier to generative AI adoption.
• Other generative AI adoption barriers include lack of capabilities (42%), unclear value proposition (36%), inadequate data/tech infrastructure (35%), and prioritization challenges (21%).

AI adoption in marketing

AI adoption in marketing is advancing steadily, with 32% of organizations fully implementing AI. 

• Nearly one-third (32%) of marketing organizations have fully deployed AI.
• 43% of organizations are already experimenting with AI and 21% are still considering how its use could benefit their operations.
• 63% of marketers are currently using generative AI while 54% are using predictive AI.
• Successful marketing groups are 2.5x more likely than less successful marketers to fully implement AI (42% to 17%).
• Only 34% of marketers are fully satisfied with the value AI has brought to their organization.
• Top uses for AI in marketing include customer relations, content creation, performance analytics, data integration, and deliverables.
• 32% of marketers find data exposure or leakage to be a top concern in AI adoption.
• Other reported concerns include copyright issues (27%), accuracy (27%), human redundancy (24%), and tech knowledge (22%). 

AI adoption in sales

AI adoption in sales nearly doubled in 2024, to 43%, as integration with existing tools drives acceptance.

• 43% of salespeople reported using AI in 2024, up from 24% in 2023.
• 87% of salespeople use AI frequently because it is integrated into tools they already use.
• 41% of sales professionals believe full AI integration would lead to unprecedented growth in their organizations.
• 25% of sales directors plan to prioritize employment candidates with knowledge of AI.
• 64% of salespeople say AI saves them 1–5 hours per week, while 40% say it saves them at least an hour per week.

Impact of AI on sales performance

AI adoption is delivering measurable performance improvements for sales teams, with three-quarters of salespeople using AI-powered Customer Relationship Management (CRM) systems reporting increased sales success.

• 75% of salespeople with AI-powered CRMs say AI adoption has resulted in higher sales.
• 64% of AI-using salespeople say AI improves their engagement with prospective clients.
• 73% of salespeople already using AI report that productivity has improved as a result.

AI usage by task

Sales professionals are adopting AI across multiple functions, with content creation leading at 42% while analytics, automation, and research follow as other application areas. 

• Of sales professionals using AI, 42% leverage it to assist with writing outreach content.
• 34% rely on AI for pipeline analysis, forecasting, and evaluating lead potential.
• 30% use AI-driven automation to streamline data entry tasks.
• 26% utilize AI for creating sales enablement copy, conducting customer research, and reformatting existing sales content.

Future outlook for AI in sales

Sales professionals anticipate widespread AI integration, with nearly three-quarters expecting AI to become standard in sales software and capable of autonomous prospect outreach by 2030.

• 73% of sales professionals feel that AI will be a standard feature in most sales software by 2030.
• 72% foresee AI reaching a level where it can independently reach out to prospects.
• 62% believe that the majority of salespeople will integrate AI into their daily work.

Concerns

Despite growing adoption, AI raises significant concerns among sales professionals, with many fearing job displacement and considering career changes due to AI advancements.

• 21% of sales professionals question how generative AI will handle their data.
• Fear of job displacement due to AI is a concern, with 59% believing their roles could be at risk.
• Due to AI advancements, 44% of sales professionals are considering a career change.
• 39% report experiencing negative effects from AI implementation.
• Despite concerns, 48% of sales directors anticipate no changes to executive staffing due to AI integration.

AI adoption in finance

AI adoption in finance has increased to more than half of financial organizations using AI.

• 58% of financial organizations were using AI in 2024, up from 37% in 2023. 
• 64% of financial leaders use AI for identifying fraudulent activities and managing risks, 57% for handling investments, and 52% for automating processes. 
• 91% of banks in the United States use AI to identify fraudulent activities, while 80% of global banks have adopted AI technology as a means to optimize their operations. 
• The global market value of AI in financial services is expected to rise from $13.7 billion in 2023 to $123.2 billion by 2032.
• 88% of financial companies implementing AI reported revenue growth, with 34% reporting growth above 20%. 
• 65% of financial organizations report ransomware attacks, underscoring the need for AI-driven fraud detection. 
• Almost 40% of AI leaders say that their organizations are piloting or using generative AI for financial reporting, while 95% of AI leaders expect to be widely using it within three years.
• 24% of financial services companies are leading AI adoption, while 58% are actively using AI but have not fully scaled yet; 18% have only just begun to implement AI.
• 36% of finance companies have adopted AI for accounting; 33% for financial planning; 18% for risk management, and 25% for treasury management. Tax operations have the lowest adoption at 18%, though this is expected to increase.

Enterprise AI adoption

Enterprise AI adoption is gaining momentum, with 82% of organizations already implementing or actively exploring AI solutions.

• 42% of enterprise-level organizations have implemented AI solutions into their operational workflows.
• Another 40% of organizations are in the exploration or experimentation phase with AI but haven't yet deployed these models. 
• 59% of organizations using or planning to use AI have increased its application since 2023. 

Enterprise AI adoption by country

Enterprises in Asian and Middle Eastern countries lead in both active AI use and implementation acceleration. 

• India leads in AI adoption, with 59% of enterprises deploying AI.
• The UAE (58%), Singapore (53%), and China (50%) also report active commercial AI implementation.
• Organizations in Spain (28%), Australia (29%), and France (26%) report comparatively lower levels of AI rollout.
• China leads in growth of AI deployment, with 85% of companies likely to accelerate their AI adoption.
• India (74%) and the UAE (72%) also demonstrate strong momentum in AI deployment.
• Businesses in the UK (40%), Australia (38%), and Canada (35%) report a lower likelihood of accelerated AI adoption.

Catalysts of AI Adoption

The top drivers for enterprise AI adoption are technology advancements, cost reduction needs, and increasing integration in business applications.

• 45% of organizations cite advances in AI tools that have improved in terms of speed and quality as their motivation for incorporating AI into their operations.
• 42% of organizations are motivated by the need to reduce operational costs and automate business processes.
• For 37% of businesses, AI adoption is occurring organically through the increasing integration of AI capabilities of common business tools.

Obstacles to AI Adoption

Leading obstacles to enterprise AI adoption are skills shortages, data complexity, and ethical considerations that impede organizational implementation efforts.

• One-third (33%) of organizations struggle with limited AI skills and expertise.
• Data complexity is a challenge for 25% of companies.
• Concerns around ethical and responsible AI use slow adoption for 23% of businesses.
• 22% of enterprises find the integration and scale of AI projects to be too complicated.
• The high cost of AI implementation is a hurdle for 21% of organizations.
• 21% of companies cite limited tools for custom AI solutions as an obstacle.
• Organizations not yet exploring generative AI cite data privacy (57%), trust and transparency concerns (43%), and a lack of implementation skills (35%) as the primary obstacles.

Industries with high AI adoption (US)

The industry with the highest AI adoption in the US is information technology, followed by professional services and educational services.

• Information technology: 18.1% of firms in this sector leverage AI. 
• Professional, scientific, and technical services: AI is used by 12% of organizations.
• Educational services: 9.1% of firms have integrated AI.

Industries with low AI adoption (US) 

The industries with the lowest AI adoption rates in the US are construction and agriculture, including forestry, fishing, and hunting.

• 1.4% of construction companies have reported adopting AI into their businesses. 
• Agriculture, forestry, fishing, and hunting 1.4% of firms use AI, particularly for precision farming, crop monitoring, and automated machinery.
• Transportation and warehousing: 1.5% of firms leverage AI.