AI adoption statistics by industries and countries: 2026 snapshot
AI adoption is the integration of various AI tools (like genAI, computer vision, agentic AI, and physical AI) into workflows, systems, and processes. In the business context, this strategic initiative is aimed at improving productivity and efficiency and redefining operational standards and boundaries.
Vention has analyzed 30+ trusted sources like Deloitte, Gartner, McKinsey, and Stanford and synthesized the insights into the Vention AI Maturity Benchmark.
This report explores how organizations worldwide are putting AI into practice, presenting an integrated view of where AI adoption and maturity stand across industries, regions, and use cases.
What is Vention?
Vention is an AI-first software development company with 20+ years of experience in custom engineering. We started with adopting AI tools within our own organization by creating an internal AI center of excellence to test emerging tools, examine the trends, risks, and possibilities, and accumulate best practices.
Now, Vention applies this profound internal knowledge to deliver intelligent solutions across 30+ industries. Our portfolio of 150+ AI projects covers the design and delivery of AI-powered solutions, as well as integration of AI into our clients’ software development lifecycles.
AI adoption statistics
By 2024, over 80% of businesses reported adopting AI. This momentum continued into 2025, with 88% of organizations using AI regularly in at least one business function. Despite this widespread adoption, only about one-third of companies have moved beyond experimentation or pilot projects to scale AI across the enterprise.
Historical vs. current AI adoption rates
AI adoption remained relatively steady between 2018 and 2022, with about 50% of companies deploying the technology in at least one business function.
Adoption began accelerating in 2023, reaching around 55%, and continued to rise sharply in 2024, with multiple studies placing it between roughly 75% and over 80% of organizations. Generative AI followed a similar trajectory, climbing from 33% to 71% within the same period.
By 2025, more than three-quarters of companies report using AI as part of their core operations. Generative AI, in particular, continues to accelerate. One clear sign of growing generative AI momentum is ChatGPT’s growth; its weekly user base expanded from 700 million to 800 million between July and December 2025.
The share of companies reporting measurable AI benefits grew from 48.4% in 2017 to 92.1% in 2023
In 2025, about 68% of CEOs say AI is reshaping key aspects of their business, and 61% believe competitive advantage increasingly depends on having the most advanced generative AI. Yet only 1% of C-suite leaders describe their generative AI initiatives as mature.
2025
61% of CEOs believe competitive advantage depends on having the most advanced genAI
2025
68% of CEOs believe AI is reshaping key aspects of their business
Enterprise AI adoption
According to Deloitte’s January 2026 report:
The shift from pilots to production remains a key bottleneck. Only 25% of respondents have moved at least 40% of their AI experiments into production environments. Despite this, momentum is strong. Around 84% of organizations report increasing their AI investments, and 78% of executives say their confidence in AI has grown.
Looking ahead, 36% of enterprises expect at least 10% of jobs to be fully automated. Adoption of agentic AI is also set to accelerate: nearly three in four companies plan to deploy it within the next two years, up from 23% today.
However, governance remains a gap, with only about 20% of organizations reporting mature frameworks for managing AI agents.
AI experts vs. the public: A widening perception gap
A 2025 survey of more than 5,400 US adults and 1,000 AI experts (professionals whose work or research directly involves AI) revealed a clear optimism divide. 47% of experts said they feel more excited than concerned about AI’s growing role in daily life, compared with just 11% of the public.
Public confidence also trails when predicting AI’s impact on the United States over the next 20 years:
Category
Positive sentiment among experts
Positive sentiment among US public
How people do their jobs
73%
23%
Economy
69%
21%
Medical care
84%
44%
K–12 education
61%
24%
The perception gap between AI experts and the public also extends to everyday use. In 2025, 79% of experts believe Americans interact with AI almost constantly or several times a day, while only 27% of US adults share that view.
AI adoption by industries
AI in healthcare
While the 2024 forecast projected that 90% of hospitals would adopt AI by 2025, the broader healthcare market has already moved in that direction: by the end of 2024, 85% of healthcare organizations were actively implementing AI.
As of early 2025, about 70% of healthcare payers and providers were actively implementing generative AI solutions to improve care delivery, efficiency, and operations.
A more granular breakdown of adoption patterns and use cases is available in Vention’s AI in healthcare statistics report.
In 2025, 80% of healthcare professionals report that AI has increased revenue in their organizations, and 45% saw measurable gains within a year. Meanwhile, 65% of healthcare executives say AI is already reshaping core business processes and clinical workflows.
Expectations for continued impact remain high. 92% of healthcare leaders believe AI will provide a competitive advantage, and 68% anticipate moderate to very high ROI from ongoing AI-driven initiatives.
In the United States, 22% of healthcare organizations have implemented domain-specific AI tools, a sevenfold increase compared with 2024 and a tenfold increase compared with 2023. Health systems lead adoption with 27%, followed by outpatient providers and payers (14%).
Record levels of AI investment in healthcare reinforce the sector’s rapid expansion. AI spending in US healthcare nearly tripled year over year, reaching $1.4 billion in 2025. The biggest spending areas include ambient clinical documentation ($600 million), coding and billing automation ($450 million), and patient engagement and prior authorization (grew up to 20× year over year). About 85% of that funding is directed toward healthcare AI startups rather than incumbent healthcare providers and vendors.
AI in financial services
AI adoption in financial services has entered a new phase of measurable scale and maturity. As of 2025, 52% of financial institutions use generative AI, up from 40% in 2023.
Top use cases for applying generative AI in financial services in 2025
% of organizations either using or assessing each use case
Customer experience and engagement
60%
Report generation, synthesis, and investment research
53%
Document processing
53%
Synthetic data generation
46%
Code assistance and software generation
44%
Creation of marketing and sales assets
43%
Enterprise search
43%
Compliance and customer onboarding
38%
Trading and portfolio optimization
38%
Pricing, risk management, and underwriting
32%
In 2025, the impact of AI adoption in financial services is already tangible.
of financial institutions enhanced employee productivity
improved customer experience
achieved new competitive advantages
report operational efficiencies
reduced annual costs by 5% or more
raised revenue by 5% or more
Barriers to AI implementation in financial services are gradually easing. Between 2023 and 2025, the share of companies citing data and privacy concerns declined from 49% to 33%, while the proportion reporting insufficient data for model training fell from 49% to 31%.
AI in education
Generative AI adoption in education continues to expand across all levels of learning. As of 2025, 86% of educational organizations report using generative AI, including 53% of education leaders, 36% of educators, and 30% of students who use it daily for teaching, planning, or school-related purposes.
Students
For students, top uses center on practical learning support:
- brainstorming assignments (37%)
- summarizing information (33%)
- getting quick answers (33%)
- initial feedback (32%)
Educators
Educators rely on AI mainly for
- brainstorming (31%)
- creating lesson plans, supporting materials, and assignments (29%)
- simplifying complex topics (24%)
- using real-time data to identify opportunities for improvement (24%).
Educational leaders
Educational leaders emphasize operational and accessibility gains, using AI to:
- improve feedback loops (36%)
- streamline operational and administrative processes (35%)
- enable student participation through accessibility tools (33%).
Confidence in using AI is high: 95% of education leaders and 78% of teachers say they can use it effectively and responsibly. Yet adoption continues to outpace institutional readiness: 71% of K–12 educators say they’ve received no professional learning on how to use AI in the classroom and fewer than half of computer science teachers feel equipped to teach it.
AI in manufacturing
As of 2025, 29% of manufacturers report using AI or machine learning at the facility or network level, while 23% remain in the pilot stage. Generative AI in manufacturing is expanding quickly: 24% of manufacturers have already scaled deployments to a similar reach, and 38% continue experimenting with pilots.
Smart manufacturing technologies powered by AI have produced measurable improvements in efficiency and operational agility across the sector. Reported benefits include:
- Up to 20% improvement in production output
- Up to 20% improvement in employee productivity
- Up to 15% in unlocked capacity
AI investment in manufacturing now ranks among the top technology priorities for the industry. 29% of manufacturers are actively investing in AI, matching the rate of adoption for cloud computing (29%) and slightly trailing data analytics (40%). Industrial IoT (27%) remains another key focus area for 2025.
AI in telecommunications
As of 2025, 97% of telecommunications companies are engaged with AI adoption, up from 90% in 2023. 49% are actively using AI in operations, while another 49% are running trials or pilots. Telecom providers report measurable benefits, including improved customer experience, enhanced employee productivity, optimized network performance, cost reduction, and new business opportunities.
AI in telecom operations is seen as a major performance driver. 77% of telecom executives say AI has improved responsiveness to market disruptions, and 75% believe AI provides a clear competitive edge.
Telecommunications investment priorities in 2025 focus heavily on AI infrastructure and customer experience. 65% of respondents plan to increase AI budgets, concentrating on infrastructure development, third-party solution integration, and staff training. Network planning and operations rank as top investment areas for 37% of companies, followed by field operations optimization (33%). Meanwhile, 44% of telecom organizations cite optimizing customer experience as a continued top priority for the third consecutive year.
AI in media and entertainment
Approximately 75% of marketers have implemented AI tools into their workflows, with 62% citing content creation as the leading use case.
52% of digital creators report that AI helps them become more creative while saving production time.
92% of content creators say they have already used generative AI in some capacity.
Large language models (LLMs) are projected to reduce up to 72% of editors’ work time, freeing capacity for more creative and strategic projects.
By 2026, generative AI in media and marketing is expected to handle repetitive tasks such as search engine optimization (SEO), content generation, and website optimization.
AI in retail and consumer goods
As of 2025, 89% of retail and consumer packaged goods (CPG) companies are actively using AI technologies or running pilot projects. About 51% of these organizations apply AI across six or more use cases, underscoring the technology’s rapid integration throughout the value chain.
AI in retail and consumer goods now spans physical stores, digital retail, and back-office operations.
Top 5 AI use cases by ROI in retail (by % of respondents)
Predictive analytics
Demand forecasting
Hyper-personalized recommendations
Customer analysis and segmentation
Marketing and advertising content generation
Performance gains reported by early AI adopters in retail and CPG:
Welspun Living case
up to 10% increase in top-line revenue for distributors and dealers within just a few months
Nestlé case
6 weeks instead of 6 months. The duration of the revised product ideation process
Alibaba case
40% increase in purchase intent thanks to transformative shifts in e-commerce and search that genAI-powered search engine enables
AI usage rate by country
AI adoption by countries
Telemetry data analysis by Microsoft gives us a clue in the share of people worldwide who have used a generative AI product. For H2 2025, the picture of AI diffusion by country is as follows:
United Arab Emirates
64%
Singapore
60.9%
Norway
46.4%
Ireland
44.6%
France
44%
Spain
41.8%
New Zealand
40.5%
Netherlands
38.9%
United Kingdom
38.9%
Qatar
38.3%
Australia
36.9%
Israel
36.1%
Belgium
36%
Canada
35%
Switzerland
34.8%
In H2 2025, the United States show just 28.3% usage rate among the working population, which makes us draw a clear line between AI infrastructure leadership and actual AI adoption.
Country-specific sentiment regarding AI adoption
Attitudes toward AI adoption remain mixed, reflecting a balance between optimism and caution among business leaders and the general public:
More concerned than excited
Equally concerned and excited
More excited than concerned
US
50%
38%
10%
Italy
50%
37%
12%
Australia
49%
38%
13%
Brazil
48%
37%
10%
Greece
47%
39%
10%
Canada
45%
45%
9%
UK
39%
46%
13%
Argentina
39%
41%
13%
Spain
39%
38%
19%
Poland
37%
42%
15%
Mexico
35%
47%
13%
France
35%
49%
15%
Netherlands
34%
48%
16%
Hungary
33%
47%
18%
Indonesia
32%
49%
14%
Kenya
31%
43%
17%
Sweden
31%
45%
22%
South Africa
30%
42%
18%
Germany
29%
53%
17%
Japan
28%
55%
16%
Turkey
26%
35%
19%
Nigeria
24%
36%
20%
Israel
21%
34%
29%
India
19%
39%
16%
South Korea
16%
61%
22%
Adoption by AI type
Agentic AI
61% of CEOs say their organization is actively adopting AI agents and preparing to implement them at scale. By 2028, one-third of interactions with genAI are predicted to use autonomous agents.
Percent of executives who anticipate clear business gains from agentic AI
Improved talent retention
Scaled employee experience
Competitive advantage
Cost reduction through automation
Improved decision-making
Early adopters of agentic AI are already validating those expectations, reporting over 50% reductions in time and effort, 20–60% productivity gains, and up to 30% faster decision speed.
Yet, enterprise-wide adoption of agentic AI remains challenging. Nearly 60% of organizations cite integration with legacy systems and managing risk and compliance as top barriers, followed closely by a lack of technical expertise.
Physical AI
Physical AI is redefining industrial operations:
Despite these advances, adoption of physical AI technologies remains complex. Experts highlight infrastructure integration (35%), workforce readiness (26%), and investment costs (21%) as the main challenges. Public sentiment shows similar caution, with concerns centered on safety (30%) and potential job displacement (26%).
Physical AI also impacts the healthcare industry: surgical robots market was evaluated at $13.69 billion in 2025, and it’s expected to reach $27.14 billion by 2030, growing at a CAGR of 14.7%.
Conversational AI
The conversational AI market is entering a phase of rapid expansion, projected to grow from $17.05 billion in 2025 to $49.8 billion by 2031, representing a compound annual growth rate of 19.6%.
Chatbot adoption among AI professionals is nearly universal: 98% report using them in some capacity. However, public engagement remains limited. Only 33% of US adults say they’ve ever interacted with an AI chatbot, and satisfaction levels mirror that divide: 61% of experts rate their experiences as very or extremely helpful, compared with just 33% of general users.
AI adoption by use cases
More than 78% of organizations now use generative AI in at least one business function, a significant increase from 55% a year earlier. Adoption spans a wide range of applications, with the top use cases including:
Marketing strategy and content support
Knowledge management
Personalization
Design development
Code creation
Automation of sales follow-up interactions
Projected impact of AI transformation
Early adopters reported boosted productivity and an average 15.2% revenue increase from generative AI in 2024, which is consistent with the 10–20% uplift projections for 2025. As tracked in the Vention AI Maturity Benchmark, the projected impact of AI transformation spans innovation and growth, customer engagement, and operations.
AI transformation of strategy and planning
- 10–20% revenue uplift
- 5–10% cost reduction
- 15–30% EBITDA impact
AI transformation of innovation and growth
- 50% faster time to market
- 50–70% increased success rate of innovation
- 20% decrease in time spent on incremental innovation activities.
AI transformation of customer and consumer engagement
- 60% reduction in content production costs
- 10–15% increase in brand net promoter score
- 20% increase in conversion rate
AI transformation of operations and supply process
- 25–31% improvement in labor efficiency
- 10–15% reduced inventory carrying costs
- 15–25% lower cost of goods sold
- 15–25% improvement in on-shelf availability
AI adoption concerns
Potential downsides of AI adoption
Both experts and the public express deep concerns about the potential downsides of AI adoption. 66% of US adults and 70% of AI experts say they are highly concerned about people receiving inaccurate information from AI systems. Bias in AI-driven decisions is another shared worry, with 55% of both groups describing it as a major concern.
Where opinions diverge is around AI’s social impact. The loss of human connection resonates more strongly with the general public: 57% say they are highly concerned that AI could reduce personal interaction, compared with just 37% of experts.
Implementation challenges
76% of business leaders reported difficulties with AI deployment in 2024, citing strategy gaps, data quality, and team readiness. Notably, 56% of companies highlighted data quality as a major barrier to AI adoption.
The concern remains evergreen: According to Gartner predictions for 2026, organizations will abandon 60% of AI projects unsupported by AI-ready data.
Spending and investments
77% of service and support leaders now feel increased pressure from executives to deploy AI, and three in four report larger AI budgets than a year ago.
CEOs expect AI investments to grow twice as fast as last year, rising from 15% to 31% for generative AI and from 13% to 31% for traditional AI. Most executives now base AI adoption on measurable ROI, with 65% prioritizing high-return use cases and 68% tracking innovation outcomes through clear performance metrics. Overall, AI spending is accelerating, projected to more than double by 2026.
AI spending worldwide ($ million), 2024–2026
Market
2024
2025
2026
AI services
259,477
282,556
324,669
AI application software
83,679
172,029
269,703
AI infrastructure software
56,904
126,177
229,825
GenAI models
5,719
14,200
25,766
AI-optimized servers (GPU and non-GPU AI accelerators)
140,107
267,534
329,528
AI-optimized IaaS
7,447
18,325
37,507
AI processing semiconductors
138,813
209,192
267,934
AI PCs by ARM and x86
51,023
90,432
144,413
GenAI smartphones
244,735
298,189
393,297
Total AI spending
987,904
1,478,634
2,022,642
The enterprise AI surge is being matched by an equally dynamic investment landscape.
In Q1 2025, global AI funding reached $68.9 billion, followed by $47.3 billion in Q2 2025. M&A activity among AI startups more than doubled compared to the five-year average, while valuations continued to climb. Some leading players, such as xAI and Decagon, achieved revenue multiples exceeding 150x.
Global AI funding
Future trends and predictions
Will AI growth hit a plateau anytime soon?
Not yet. AI continues its steep ascent: enterprise worker access grew by 50% within 2025. Rather than slowing, AI is becoming more deeply embedded in core infrastructure.
What directions will dominate companies’ AI roadmaps?
Two key areas are emerging. Multimodal AI (i.e., systems that can understand and combine text, images, audio, and video) is expected to expand from a $2.4 billion market in 2025 to nearly $99 billion by 2037.
At the same time, multi-agent systems are emerging as the next frontier. AI agents are already among the most rapidly advancing technologies on Gartner’s 2025 Hype Cycle and are increasingly viewed as the backbone of intelligent automation strategies. In fact, 68% of CEOs say their future workforce models will integrate human employees and AI agents or robots.
Are shifts in geographic leadership on the horizon?
By 2030, the Chinese AI market is projected to nearly match North America’s scale: $70.4 billion versus $72.6 billion, signaling intensifying competition between the world’s two major AI powerhouses.
Will AI’s economic impact become tangible?
By 2038, generative AI alone is expected to make a measurable contribution to global GDP growth. In consumer industries, its potential boost could reach $586 billion in the United States, $166 billion in Japan, and $122 billion in Germany, each adding roughly 0.3 percentage points to national GDPs.
Emerging markets may experience even stronger gains. Brazil’s economic impact could reach 0.7%, while advanced economies such as France (+0.5%), the UK (+0.4%), and Canada (+0.4%) are also poised for substantial increases.
AI is evolving at an unprecedented pace, so check back often as we’ll keep updating the numbers to help you stay ahead of the trends.
If you’d like a quote or deeper insights from one of our experts, feel free to reach out to us here.
Sources:
ABI Research
CB Insights
Deloitte
Forbes
Gartner
IBM
KPMG
Markets & Markets
McKinsey
Menlo Ventures
Microsoft
National Education Association
NVIDIA
Pew Research Center
Stanford University
World Economic Forum