In focus: AI statistics

We’ve collated the latest AI statistics, so you don’t have to.

Check out AI’s impact on the economy, the workplace, employee productivity and marketing sectors, below.

AI development statistics

• AI deployments are taking an average of less than 8 months and organisations are realising value within 13 months (source: Microsoft)
• More than half of organisations expect to build custom industry and line-of-business applications within the next 24 months (source: Microsoft)
• Global AI adoption among desk workers grew from 20% in September 2023 to 32% in March 2024, but growth has slowed over the past three months, with France seeing just a 2 percentage point increase (from 31% to 33%) and the US seeing only a 1 percentage point increase (from 32% to 33%) (source: Slack)
• 37% of UK IT professionals at large organisations report active AI deployment, with an additional 41% exploring the technology (source: IBM)
• 32% of UK enterprises actively implementing generative AI, with another 46% exploring it (source: IBM)
• ChatGPT now has more than 200 million weekly active users, which is twice as many as it had in November 2023 (source: Axios)
• OpenAI’s ChatGPT Enterprise has been implemented at over 260 companies (source: VentureBeat)
• Moderna has deployed ChatGPT enterprise products to all employees and is using OpenAI’s advanced data analysis tools, leading to an average reduction of 30 days in the drug approval process (source: VentureBeat)
• 89% of SMB leaders use digital tools to find new customers, and 88% use them to retain existing customers. Additionally, 78% use them to work productively with employees, and 72% use them to hire new team members (source: Connected Commerce Council)
• Usage of OpenAI’s automated API has doubled since the release of GPT-4o mini in July 2024 (source: Axios)
• Usage of Meta’s open-source Llama models at major cloud service providers doubled between May and July 2024 following the release of Llama 3.1. (source: Axios)
• 72% of organisations have increased spending on AI and emerging technologies in the past three years, while 77% plan to continue investing in AI and emerging technologies over the next three years (source: Autodesk)
• 68% of organisations have moved only 30% or fewer of their generative AI experiments into production. (source: Venture Beat)
• 41% of organisations struggle to define and measure the exact impacts of generative AI efforts. (source: Venture Beat)
• Only 16% of organisations produce regular reports for their CFOs detailing the value created by generative AI. (source: Venture Beat)
• In 2023, most enterprises tested only 1–2 generative AI models (often OpenAI’s). By the end of 2024, enterprises are increasingly experimenting with multiple models, often using fine-tuned open-source models in production alongside closed-source models (source: Andreessen Horowitz)
• By 2027, more than 50% of enterprises will have implemented a responsible AI governance program, and the number of companies using open-source AI will increase tenfold (source: Venture Beat)
• Smaller language models with 1 billion to 10 billion parameters are becoming more common in resource-constrained environments, such as PCs and mobile devices, offering acceptable accuracy (source: Venture Beat)
• Global excitement about AI dropped 6 percentage points, from 47% to 41%, driven by a 9 percentage point drop in the US (from 45% to 36%) and a 12 percentage point drop in France (from 53% to 41%) (source: Slack)
• 76% of professionals say they trust AI for their industry and have embraced it to enhance productivity, improve efficiency, and achieve sustainability goals (source: Autodesk)
• 79% of global business leaders, futurists, and experts across Design and Make industries agree that AI will make their industry more creative. (source: Autodesk)
• 78% of global business leaders, futurists, and experts across Design and Make industries believe AI will enhance their industry, and the same percentage express confidence that their company will make the right decisions regarding AI (source: Autodesk)
• Performance is often highest when relevant information occurs at the beginning or end of the input context, and significantly degrades when models must access relevant information in the middle of long contexts, even for explicitly long-context models (source: Cornell University )
• The global artificial intelligence market size was valued at USD 136.55 billion in 2022 (source: Grand View Research)
• The global artificial intelligence market is projected to expand at a compound annual growth rate (CAGR) of 37.3% from 2023 to 2030 (source: Grand View Research)
• The chance of unaided machines outperforming humans in every possible task was estimated at 10% by 2027 and 50% by 2047 (source: AI Impacts)
• The aggregate forecasts give at least a 50% chance of AI systems achieving several milestones by 2028, including autonomously constructing a payment processing site from scratch, creating a song indistinguishable from a new song by a popular musician, and autonomously downloading and fine-tuning a large language model (source: AI Impacts)
• The chance of all human occupations becoming fully automatable was forecast to reach 10% by 2037 and 50% as late as 2116 (source: AI Impacts)
• Between 37.8% and 51.4% of researchers who had published in top-tier AI venues gave at least a 10% chance to advanced AI leading to outcomes as bad as human extinction (source: AI Impacts)
• 3% of researchers who had published in top-tier AI venues thought good outcomes from superhuman AI are more likely than bad, with 48% of these net optimists giving at least a 5% chance of extremely bad outcomes such as human extinction, and 59% of net pessimists giving 5% or more to extremely good outcomes (source: AI Impacts)
• More than half of researchers who had published in top-tier AI venues suggested that “substantial” or “extreme” concern is warranted about six different AI-related scenarios, including the spread of false information, authoritarian population control, and worsened inequality (source: AI Impacts)
• Only 23% of organisations feel highly prepared to address generative AI-related risk management and governance challenges (source: Venture Beat)

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AI and economic impact statistics

• Analysts expect 37% revenue growth for semiconductor firms from current levels by the end of 2025 due to strong AI-related investment growth (source: Seeking Alpha)
• Since the release of ChatGPT, analysts have upgraded their end-2025 revenue projections for semiconductors by $187 billion (0.7% of US GDP) and for AI hardware enablers by $139 billion (0.5% of US GDP) (source: Seeking Alpha)
• Spending on AI has increased by 130%, with 72% of companies planning further investment in 2025 (source: AI at Wharton)
• More than 90% of CIOs say that managing costs limits their ability to derive value from AI initiatives (source: Venture Beat)
• Software vendors have increased their prices by up to 30% due to the integration of AI into their product pipelines (source: Venture Beat)
• 75% of CEOs say AI will be the most impactful technology for their industry, up from 21% in 2023 (source: Venture Beat)
• Budgets for generative AI projects are expected to almost triple from 2023 to 2025, rising from an average of 5% of IT budgets to 4.3% (source: TechRadar)
• 26% of companies with more than $5 billion in revenue plan to allocate more than 10% of their IT budgets toward generative AI by 2025 (source: TechRadar)
• 67% of organisations are increasing investments in generative AI due to strong early value from its use (source: Venture Beat)
• 75% of organisations have increased investments in data lifecycle management for generative AI (source: Venture Beat)
• A new McKinsey survey reveals that 42% of surveyed organizations report cost reductions from implementing AI (including generative AI), and 59% report revenue increases (source: Stanford University)
• For every $1 invested in generative AI, companies are seeing an ROI of $3.7x, with the top leaders realising an ROI of $10.3 (source: Microsoft)
• IDC predicts that business spending to adopt AI will have a cumulative global economic impact of $19.9 trillion through 2030 and drive 5% of global GDP in 2030 (source: Microsoft)
• The ROI of generative AI is highest in Financial Services, followed by Media & Telco, Mobility, Retail & Consumer Packaged Goods, Energy, Manufacturing, Healthcare, and Education (source: Microsoft)
• More than 90% of CIOs say that managing costs limits their ability to derive value from AI initiatives (source: Venture Beat)
• Generative AI use cases deliver the value across banking ($200 billion to $340 billion annually) and retail and consumer packaged goods ($400 billion to $660 billion annually) (source: McKinsey)
• Multinational organisations in Ireland use 30% more generative AI compared to indigenous Irish organisations, creating opportunities to drive competitiveness and boost Ireland’s position as a global technology hub (source: Microsoft)
• “Total economic benefits of generative AI—including the major use cases we explored and the myriad increases in productivity that are likely to materialize when the technology is applied across knowledge workers’ activities—amounts to $6.1 trillion to $7.9 trillion annually” (source: McKinsey)
• Generative AI could potentially raise global GDP by 7%, or almost $7 trillion, and increase productivity growth by 5 percentage points over a decade (source: Goldman Sachs)
• McKinsey’s insights indicate that generative AI could potentially add $2.6 trillion to $4.4 trillion annually to the global economy, bolstering the impact of all artificial intelligence by 15 to 40 percent (source: McKinsey)
• AI could contribute up to $15.7 trillion to the global economy in 2030. Of this, $6.6 trillion is likely to come from increased productivity and $9.1 trillion is likely to come from consumption-side effects (source: PwC)
• The majority of a Centre for Economic Policy Research (CEPR) panel (64%) believes that AI will increase global economic growth to 4–6% per annum over the upcoming decade, while the remainder (36%) thinks that AI will have no significant effect on global growth (source: CEPR)
• The majority of Centre for Economic Policy Research (CEPR) panellists express a great degree of uncertainty regarding their predictions about the impact of AI on global economic growth and unemployment in high-income countries (source: CEPR)
• AI specialist jobs command up to a 25% wage premium on average, including 14% in the UK, 11% in Canada, 7% in Singapore, and 6% in Australia (source: Irving Wladawsky-Berger)
• Data base designers and administrators command a 53% wage premium in the US and 58% in the UK, while financial analysts have a 33% wage premium in the US and 32% in the UK (source: Irving Wladawsky-Berger)
• 48% of global C-suite leaders are using freelancers to jumpstart delayed AI projects (source: Forbes)
• 39% of C-suite leaders report that leveraging freelancers has doubled their innovation outcomes (source: Forbes)
• 80% of leaders leveraging freelance talent stated it is essential to their business, and 38% of leaders not currently using freelancers intend to do so in the coming year (source: Forbes)
• In tasks related to communication, creativity, and data analysis, generative AI boosted the performance of workers from both the US and South Africa. However, the performance gains were more substantial for South African workers, reducing the skill gap between them and US workers. US workers still scored higher overall, even after both groups used generative AI (source: Harvard Business Review)
• South African remote workers, when using generative AI, delivered 40% more value per dollar spent compared to US workers using generative AI. Compared to US workers not using generative AI, South African workers provided 80% more value for money (source: Harvard Business Review)
• Goldman Sachs Research suggests that advances in AI could affect the equivalent of 300 million full-time jobs globally, with roughly two-thirds of U.S. occupations exposed to some degree of AI automation (source: Goldman Sachs)
• Most Centre for Economic Policy Research (CEPR) panellists (63%) believe that AI will not affect employment rates in high-income countries over the upcoming decade, while the majority of the remainder (27%) think that developments in AI could increase unemployment in high-income countries, while only two panellists believe that AI could decrease unemployment in high-income countries over the upcoming decade (source: CEPR)
• Accenture’s estimate suggests that 40% of working hours could be influenced by generative AI (source: Bloomberg UK)
• By 2027, the Design and Make industries, which employ nearly 300 million people worldwide, will represent $30 trillion in global value (source: Autodesk)
• 71% of global business leaders, futurists, and experts across Design and Make industries consider digital maturity a top attractor of talent in their industries. (source: Autodesk)
• 46% of top enterprise leaders indicated a preference or strong preference for open-source AI models in 2024, compared to a closed-source market share of 80–90% in 2023. The shift reflects the growing interest in control, data security, and customisation with open-source tools (source: Andreessen Horowitz)
• Model APIs and fine-tuning spend are projected to grow to a $5 billion annual run rate by the end of 2024, up from an estimated $1.5–2 billion run rate in 2023. Enterprises are expected to be a major driver of this growth (source: Andreessen Horowitz)

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AI and marketing statistics

• AI adoption in Marketing and Sales tripled, rising from 20% in 2023 to 62% in 2024 (source: AI at Wharton)
• AI usage in Procurement surged from 50% to 94%, in Product Development from 40% to 78%, in Operations from 16% to 50%, and in HR, Purchasing, and Procurement more than doubled (source: AI at Wharton)
• 32% of consumers across markets have a more positive opinion of generative AI tools like ChatGPT and Gemini compared to a year ago, while 22% have a more negative opinion and 31% say their perception of the tools hasn’t changed at all (source: YouGov)
• Men are more likely than women (36% vs 28%) to have a more positive opinion of generative AI tools now compared to last year, while 24% of women have a more negative opinion compared to 22% of men, and 31% of both men and women say their opinion hasn’t changed (source: YouGov)
• 40% of Americans say their perception of generative AI tools has become more negative in the past year, followed by 32% of Britons and 30% of Canadians, while only 13% of Singaporeans report a more negative view, the lowest in Asia (source: YouGov)
• 39% of Danes, and 38% each of Swedes, Germans, and Spaniards, say their perception of generative AI tools hasn’t changed, with 37% of Singaporeans leading Asia in reporting no change in opinion (source: YouGov)
• Over 60% of people aged 16–34 (Gen Z and younger millennials) have used generative AI, compared to only 14% of those aged 55–75 (older Gen Xers and baby boomers) (source: Fortune)
• Men are more likely to use generative AI than women, with 43% of men reporting usage compared to 28% of women (source: Fortune)
• Deloitte Digital’s research highlights that one in four companies are already using generative AI (Gen AI) in their marketing operations, demonstrating the pace at which AI is being adopted for creative endeavours (source: Deloitte Digital)
• Early adopters of Gen AI are three times as likely to have a formal, analytics-driven process to balance content supply and demand, a fully functioning project planning process, and a very high level of automation for content distribution (source: Deloitte Digital)
• 56% of early adopters conduct A/B testing on Gen AI-produced content “most of the time,” and 62% of teams using Gen AI extensively consider themselves expert or highly skilled (source: Deloitte Digital)
• Despite the early stage of adoption, 59% of early adopters are already seeing higher-quality content and tagging, with 56% reporting higher employee productivity and 51% observing a higher volume of content produced (source: Deloitte Digital).
• Early adopters of Gen AI are capable of meeting content demands 5 times more often than companies with no Gen AI plans, saving the average content marketing employee 11.4 hours per week (source: Deloitte Digital)
• Gen AI is reported to be involved in the development of 46% of content by companies that have implemented it. However, these firms are primarily using AI to improve content rather than generate it entirely (source: Deloitte Digital)
• Up to 24% of corporate press release text is generated or modified by large language models (source: The Widespread Adoption of Large Language Model-Assisted Writing Across Society)
• Nearly 14% of UN press release content is either generated or modified by large language models (source: The Widespread Adoption of Large Language Model-Assisted Writing Across Society)
• More than 3 in 4 early adopters of gen AI in marketing remain concerned about potential brand risks such as intellectual property issues, cultural insensitivity, impersonal experiences, and reduced creative quality (source: Deloitte Digital)
• In a BCG survey of over 200 CMOs, approximately 70% are actively using gen AI, while 19% are currently testing its capabilities (source: BCG)
• A significant 67% of CMOs are focusing on personalisation through gen AI, 49% are using it for content creation, and 41% for market segmentation (source: BCG)
• 93% of CMOs report a positive or very positive improvement in work organization, and 91% see a positive or very positive impact on work efficiency due to GenAI (source: BCG)
• Gen AI is enhancing the entire customer life cycle, impacting every stage from awareness to advocacy (source: Insider Intelligence)
• 66% of marketers using gen AI report a positive return on investment, with benefits including cost efficiencies, improved performance, and faster creative cycles (source: Insider Intelligence)
• 24% of workers use generative AI for brainstorming (source: HRreview)

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AI and productivity statistics

• Academic studies suggest a 23% average uplift to productivity in areas where generative AI has been deployed, while company anecdotes suggest a 30% productivity gain (source: Seeking Alpha)
• Sectors with high AI penetration are experiencing 8x greater labour productivity growth compared to sectors with low AI penetration (source: Irving Wladawsky-Berger)
• 96% of C-suite executives expect AI to boost productivity (source: Forbes)
• Among employees who use AI at work, 72% say it makes them more productive (source: CNBC)
• Access to AI tools increases customer support agent productivity by 14% on average (source: NBER)
• Consultants using AI were significantly more productive (they completed 12.2% more tasks on average, and completed task 25.1% more quickly), and produced 40% higher quality results (source: SSRN)
• An estimated 40% of working hours are expected to be supported or augmented by language-based AI, indicating a significant transformation in the workforce (source: Accenture)
• 41% of companies state that the ability to implement or work with AI will be the top technical skill prioritised during hiring decisions over the next three years (source: Autodesk)
• Nearly 44% of CFOs believe that while AI will eventually save them money, it will cost more than it saves over the next 12 months (source: CNBC)
• Workers from within the gen Z and millennial generations who have used AI in their jobs account for 37% and 35% respectively, compared to 25% of Gen Xers and 17% of baby boomers (source: CNBC)
• AI software is used by 41% of Asian employees, 38% of Black, 36% of Hispanic workers, and 23% of white workers (source: CNBC)
• 63% of workers report that generative AI tools have positively impacted their productivity. 7% report a significant increase in productivity (S
• source: The Conference Board)
• 55% of workers believe current output from generative AI matches the quality of experienced or expert human workers (source: The Conference Board)
• 33% of employees expect AI to replace elements of their job in a positive way—e.g., by freeing up time for more valuable or creative tasks (source: The Conference Board)
• 67% of workers who use generative AI tools report increased job satisfaction (source: HRreview)
• 27% of UK workers would prefer to spend the time saved by generative AI to enhance their work-life balance (source: HRreview)
• 82% of SMB leaders who are already using AI tools report positive outcomes on their businesses (source: Connected Commerce Council)
• 64% of SMBs either currently use AI tools or plan to adopt them in the next two years. Among SMBs led by people of colour, the figure is 71%, and among veteran-owned SMBs, it is 74% (source: Connected Commerce Council)
• SMB leaders consider training employees to use AI a priority, with 74% of those already using AI tools highlighting this need (source: Connected Commerce Council)
• When asked how they plan to use AI tools in the next two years, the most common responses among SMB leaders included saving time and money (60%), helping their business grow (59%), boosting efficiency (58%), and improving customer service (57%) (source: Connected Commerce Council)
• Atento added OpenAI’s tech to its customer service function and as early as the pilot stage recorded a 20%+ increase in customer satisfaction in the first few weeks (source: Microsoft)
• KPMG Australia added GPT-4 to its internal search tool and boosted search quality from 50% to 91%, with results delivered in under a second (source: Microsoft)
• Amdocs produces software to help telecoms companies manage their billing and customer services. The use of generative AI, the company says, has reduced the handling time of customers’ calls by almost 50% (source: The Economist)
• Nasdaq a financial-services firm, helps financial-crime sleuths gather evidence to assess suspicious bank transactions. They observed a decrease in the time required to assess suspicious bank transactions from 30-60 minutes to 3 minutes with the aid of generative AI (source: The Economist)
• Bank of New York Mellon uses an AI system that produces draft reports overnight. “So rather than getting up at four in the morning to write research, they get up at six,” the bank says (source: The Economist)
• L’Oréal experienced productivity increases of up to 10-15% for some of their brands that deployed generative AI (source: The Economist)
• Microsoft’s Work Trend Index report found that 77% of Copilot users don’t want to give it up, and 70% claimed it made them more productive with 68% saying it improved the quality of their work (source: CNBC)
• ChatGPT-4 is capable of generating 200 ideas in about 15 minutes when interacted with by a human, compared to a single human generating about five ideas in the same time frame (source: SSRN)
• A professional working with GPT-4 can produce ideas at a rate of 800 ideas per hour, at a cost of around USD 0.63 each, or USD 7.50 per dozen (source: SSRN)
• Using GPT-4, the cost for generating 800 ideas was about $20 at the time of the study, in contrast to a human working alone who could only generate 20 ideas at an approximate cost of $25 each (source: SSRN)
• For the task of focused idea generation, a human employing GPT-4 is about 40 times more productive than a human working alone (source: SSRN)
• Among organisations with a generative AI-first policy, 71% report seeing productivity increases, compared to 42% of firms that prohibit generative AI (source: Microsoft)
• Consultants using AI finished 2% more tasks on average, completed 25.1% more quickly (source: SSRN)
• Novice and low-skilled workers experienced a 34% improvement in productivity when using AI tools, with minimal impact on experienced and highly skilled workers (source: NBER)
• 45% say the quality of AI output is equal to an experienced worker, 31% say the quality of AI output is equal to a novice worker and 10% say the quality of AI output is equal to an expert worker (source: The Conference Board)
• 92% of workers find generative AI tools to be useful (source: HRreview)
• 26% of workers experience heightened productivity and reclaimed time due to generative AI tools (source: HRreview)

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AI and the workplace statistics

• Only 1% of US firms currently utilise AI to produce goods or services, a slight increase from 5.9% in the third quarter (source: Seeking Alpha)
• Large companies with over 250 employees have the highest AI adoption rate at 10% and expect the largest increase in adoption over the next six months (source: Seeking Alpha)
• AI adoption has doubled in small to mid-sized businesses over the past year (source: Seeking Alpha)
• In job postings, LLM-assisted writing makes up just under 10% in small firms, with even higher usage in younger firms (source: The Widespread Adoption of Large Language Model-Assisted Writing Across Society)
• Generative AI usage jumped from 55% in 2023 to 75% in 2024 (source: Microsoft)
• 99% of executives plan to invest in AI this year, with 72% prioritising a “significant” investment, and 97% feeling some level of urgency to incorporate AI into business operations (source: Slack)
• 72% of leaders report using generative AI at least once a week, up from 37% in 2023 (source: AI at Wharton)
• Nearly half of organisations are hiring Chief AI Officers (CAIOs) to lead strategic initiatives (source: AI at Wharton)
• 60% of organisations have already hired a Chief AI Officer, and 26% more plan to do so by 2026 (source: Amazon Press Center)
• By 2025, 30% of enterprises will have implemented an AI-augmented and testing strategy, up from 5% in 2021 (source: Venture Beat)
• By 2026, more than 100 million humans will interact with robo or synthetic virtual colleagues, and nearly 80% of prompting will be semi-automated (source: Venture Beat)
• 60% of CIOs are currently responsible for leading AI strategies in their organisations (source: Venture Beat)
• 92% of Fortune 500 companies are using OpenAI’s products (source: Axios)
• 85% of businesses reported they were not currently using AI, and 83% are not planning to adopt AI within the next three months (source: ONS)
• In the UK, 60.2% of working people use AI tools at least once a month, of that 28.3% use it at least once every few days (source: Definition)
• LLM adoption at work among US adults rose from 30.1% in December 2024 to 43.2% by March and April 2025 (source: The Labor Market Effects of Generative Artificial Intelligence)
• ChatGPT Enterprise is used by more than 150,000 employee users (source: VentureBeat)
• 44% of workers have never used generative AI, and 56% use it for work-related tasks at least occasionally (source: The Conference Board)
• PwC is deploying ChatPwC to 75,000 workers by the end of 2023 (source: CNBC)
• Deloitte is rolling out a generative artificial intelligence chatbot to 75,000 employees across Europe and the Middle East to create PowerPoint presentations and write emails and code in an attempt to boost productivity (source: Financial Times)
• In 2024, more than half (55%) of top technology officers plan to purchase enterprise-level generative AI software, such as Microsoft Copilot, in the next six months (source: CNBC)
• More than half (59%) of the tech officers surveyed report an acceleration in their company’s new investments in artificial intelligence capabilities (source: CNBC)
• In 2024, Gartner predicts that enterprises will spend $114.8 billion on security and $21.8 billion on generative AI (source: CNBC)
• A recent Gartner survey found that 82% of IT buyers said Microsoft 365 Copilot was in their top three of the “most valuable” new features (source: CNBC)
• A staggering 98% of business leaders believe that AI foundation models are critical to their organisational strategies for the next three to five years (source: Accenture)
• The McKinsey Global Institute predicts that around 70% of companies will adopt at least one type of AI technology by 2030 (source: CEPR)
• 49% of organisations in Ireland are already using generative AI in some form at this early stage of its availability (source: Microsoft)
• The average spend on generative AI across foundation model APIs, self-hosting, and fine-tuning models in 2023 was $7 million per enterprise. Enterprises plan to increase this spend by 2x to 5x in 2024 to support deploying more workloads to production (source: Andreessen Horowitz)
• In 2023, most generative AI spend came from “innovation” budgets. In 2024, however, less than 25% of enterprises expect their generative AI spend to come from innovation budgets. More budgets are being reallocated to permanent, recurring software expenses (source: Andreessen Horowitz)
• Nearly half of desk workers (48%) would feel uncomfortable admitting to their manager that they used AI for workplace tasks, with 47% citing fear of AI being seen as cheating, 46% fearing being seen as less competent, and 46% fearing being seen as lazy (source: Slack)
• 45% of desk workers report not having explicit permission to use AI at work, and 30% have had no AI training at all, including self-directed learning or experimentation (source: Slack)
• 56% of organisations already have a generative AI training plan in place and 19% plan to develop one by the end of 2025 (source: Amazon Press Center)
• 68% of desk workers believe the average college graduate today has more AI skills than the average employee at their company, with workers in their first job being twice as likely to think of themselves as AI experts compared to more experienced employees (source: Slack)
• 3 out of 4 desk workers consider an employer’s ability to provide AI tools a factor in their job search, with nearly two in five saying they prefer AI-savvy employers (source: Slack)
• 70% of employees who use ChatGPT hide their usage from their employers (source: TechRadar)
• 9% of employees have admitted to pasting their company data into ChatGPT, leading to hundreds of confidential information leaks to the chatbot each week at the average company (source: TechRadar)
• 77% of employees using AI say it has added to their workload rather than reducing it, and 40% of employees feel their company is asking too much of them regarding AI expectations (source: Forbes)
• 47% of employees using AI state they don’t know how to achieve the expected productivity gains employers anticipate (source: Forbes)
• 42% of employees are concerned about the impact of AI technology on their jobs (source: CNBC)
• Workers earning under $50,000 a year are 47% concerned about AI’s impact, whereas those making between $50,000 and $99,000 show a 39% concern, and it’s 36% concern for those earning $100,000 or more (source: CNBC)
• 60% of those using AI regularly are worried about its impact on their job, versus 35% of those who don’t use AI at work (source: CNBC)
• Nearly half of the tech executives surveyed by CNBC indicate that up to 25% of their employees are already using generative AI in their work (source: CNBC)
• 44% of business leaders report that there will be layoffs in 2024 resulting from AI efficiency (source: CNBC)
• 42% of UK workers surveyed use generative AI tools at least once a week (source: HRreview)
• 10% of workers rely on generative AI tools daily (source: HRreview)
• 63% of Generation Z workers use generative AI at least once a week, compared to 22% of those aged 55 and over (source: HRreview)
• Even among organisations that lack an AI policy, 40% of employees still report their managers are fully aware that they’re using AI tools at work (source: The Conference Board)
• 26% of US workers report that their organisation has a policy related to the use of generative AI. 23% indicate that a generative AI policy is under development within their company. 71% of workers who use generative AI claim their management is aware of their AI tool usage. 46% indicate that their management is fully aware of their generative AI usage and 34% of workers say their organisation does not have any AI policy (source: The Conference Board)
• A shadow AI culture is emerging: 27% of leaders report using publicly available/free generative AI tools in their role, and 25% believe their employees are doing the same. Additionally, 8% are aware of employees knowingly using generative AI software in direct violation of their organisation’s policies (source: Microsoft)
• 60% of consumers in the UAE have developed a more positive perception of generative AI tools this year compared to last, followed by 59% of both Indians and Indonesians, while 29% of Italians are the most likely in Europe to report a more positive opinion (source: YouGov)
• Only 17% of Americans say their perception of generative AI tools is now more positive compared to last year, the lowest across all surveyed markets (source: YouGov)
• The proportion of British people who use generative AI at work increased by 66% in a year, rising from 14% of the workforce in the previous year (source: Fortune)
• Among the 7 million British workers who have used generative AI at work, only 27% reported that their employer officially encouraged its use (source: Fortune)
• Over a quarter (28%) of workers are currently using generative AI at work, and over half without the formal approval of their employers (source: Salesforce )
• More than 34% of organisations are willing to implement generative AI quickly, despite the risks of negative outcomes (source: TechRadar)
• BlackBerry found that 75% of organisations are considering or implementing bans on generative AI applications like ChatGPT in the workplace (source: Blackberry)
• South Cambridgeshire District Council has been testing a shorter working week (achieved because of AI efficiencies) since January 2023 – staff welfare surveys suggest employees were enjoying better mental health thanks to the four-day working week (source: BBC)
• 39% of professionals state that AI will help automate mundane, repetitive tasks, and 35% expect AI to supplement a skills gap (source: Autodesk)
• 90% of leaders agree that AI enhances employee skills, up from 80% in 2023, while concerns about job replacement have eased to 72%, down from 75% (source: AI at Wharton)
• 30% of AI users indicated a lack of specialised AI skills in-house, and 26% said they lacked employees with the skills to learn and work with AI (source: Microsoft)
• 76% of desk workers feel urgency to become AI experts, with industry trends and personal goals being the top motivations (source: Slack)
• 48% of freelancers report being “somewhat” or “highly” skilled at using AI, and 34% use AI tools at least 1 to 2 days per week (source: Forbes)
• Only 40% of leaders have a high level of awareness of the AI skills present within their workforce (source: Forbes)
• There is a disparity in workplace training on generative AI, with 58% of 18-24-year-olds having received training, versus only 17% of those over 55 (source: HRreview)
• The primary way organisations are monetising AI is through productivity use cases, with 43% saying these use cases have provided the greatest ROI (source: Microsoft)
• One enterprise reported saving 90% of costs in customer service by using LLM-powered tools (~$6 saved per call served) and, as a result, increased its generative AI investment eightfold (source: Andreessen Horowitz)
• Without generative AI, completing the same work would require nearly 100 times the current headcount (source: Market Watch)
• By late 2024, around 18% of financial consumer complaint text is assisted by large language models, with usage spread across different regions and slightly higher in urban areas (source: The Widespread Adoption of Large Language Model-Assisted Writing Across Society)
• Generative AI improved the productivity, quality, and consistency of work for both US and South African workers. US-based evaluators rated generative AI-assisted outputs as higher quality than non-AI-assisted work. Variability in work quality also decreased, making generative AI-assisted outputs more consistent and reliable (source: Harvard Business Review)
• US evaluators were unable to distinguish whether work completed with the help of generative AI came from US-based or South African remote workers, achieving a “perfect substitution” rate. Without generative AI, evaluators could correctly identify the origin of the work 60% of the time (source: Harvard Business Review)
• US workers were paid 50% more than their South African counterparts. Based on this amount, we can calculate a quality score per dollar spent on remote work. This calculation showed that South African workers using gen AI provided 40% more value for money than U.S. workers using gen AI, and 80% more than U.S. workers not using gen AI (source: Harvard Business Review)
• Employees at Onix, a global cloud consulting company, who are saving the equivalent of an entire day of work every month using Gemini, or the team at Sports Basement, a sporting goods retailer, who’ve reduced the time it takes to craft responses to customer support requests by 30-35%. (source: Google Workspace)
• 80% of city employees in Yokosuka, Japan, reported increases in productivity after gaining access to ChatGPT (source: OpenAI)
• 40% of public sector time could be supported by generative AI (source: The Alan Turing Institute)
• Public sector workers spend on average 30 minutes a day on emails and using generative AI to help with drafting could cut this time by 70% (source: The Alan Turing Institute)
• Education staff spend up to 49% of their time on teaching tasks that generative AI could support and spend 100 minutes a day preparing lesson plans, 75% of which could be supported by generative AI (source: The Alan Turing Institute)
• 38% of frontline workers’ tasks could be supported by generative AI compared to 46% for non-frontline workers (source: The Alan Turing Institute)
• A trial involving 20,000 civil servants showed they could save nearly 2 weeks a year by using AI, which is about 26 minutes a day, the same as giving 1,130 people a whole year back to focus on higher-value tasks like innovation or public service rather than admin work (source: uk)
• All surveyed early adopters report a positive ROI on their gen AI investments, averaging a 12% return (source: Deloitte Digital)
• Laura Gilbert, chief analyst and data science director at Downing Street, said the UK government had found a lot of “low-hanging fruit” where AI could drive significant efficiencies. While there was a general target for a 3.55 times return on investment on AI, she said “some of the early tools are more like a 200 times return on the investment” (source: FT)
• AI assistance increased agent productivity by 14% at a call centre, with the most significant impact on less experienced workers (source: Standford University, HAI)
• 47% of organisations believe generative AI will enhance productivity, while 17% hold opposing views (source: Microsoft)
• Generative AI exposes around 25% of workers in the OECD, meaning 20% or more of their job tasks could be completed at least 50% faster with AI assistance (source: OECD)
• Jobs with significant AI exposure are growing 27% more slowly than other jobs in occupations like customer sales and service, administrative and commercial managers, and IT and business professionals (source: Irving Wladawsky-Berger)
• Financial services has a 8x higher share of jobs requiring AI skills compared to other sectors, professional services has a 3x higher share, and information and communications has a 5x higher share (source: Irving Wladawsky-Berger)
• AI specialist jobs have grown 5x faster than all other jobs since 2016 (source: Irving Wladawsky-Berger)
• Demand for skills complementing AI has seen rapid growth in sectors like performing arts, sports, and recreation with 155% growth, personal care and services with 82% growth, energy and utilities with 58% growth, and environmental roles with 48% growth (source: Irving Wladawsky-Berger)
• Skills with high AI exposure have seen declines in demand, such as information technology by 26%, design by 23%, sales by 20%, and analysis by 14% (source: Irving Wladawsky-Berger)
• 41% of senior executives expect to have smaller workforces within five years due to AI technology, according to a survey of 2,000 large companies worldwide (source: Reuters)
• A 2023 World Economic Forum study found that 25% of companies expected AI to cause job losses, while 50% believed the technology would create new roles (source: Reuters)
• A recent report from ResumeBuilder indicates that 37% of business leaders acknowledged that AI replaced workers in 2023. They also predict 44% claim there will be layoffs in 2024 resulting from AI efficiency (source: CNBC)
• AI could create 170 million new jobs globally while eliminating 92 million positions, resulting in a net increase of 78 million jobs by 2030 (source: World Economic Forum)
• Asana’s research found that employees perceive 29% of their work tasks as replaceable by AI (source: CNBC)
• In the EU, 61% of jobs are expected to work together with generative AI, 32% of jobs are likely to remain unaffected by generative AI, and only 7% of jobs are deemed highly exposed to generative AI, leading to some job closures. 74% of workers in European countries see productivity-enhancing effects of generative AI, and 43% of workers in European countries expect AI to positively impact their job (source: Implementing Consulting Group)
• 72% of all SMB leaders say privacy, trust, and safety are top priorities when it comes to AI tools. This increases to 84% among those already using AI in their businesses (source: Connected Commerce Council)
• 63% of SMB leaders express concerns about being targeted by a cyber attack, rising to 78% among those already using AI tools. However, only 38% of SMB leaders have a cybersecurity plan in place (source: Connected Commerce Council)
• 60% of SMB leaders believe AI tools will increase their business’s productivity over the next two years. Among those already using AI, this figure rises to 82% (source: Connected Commerce Council)
• 55% of SMB leaders say AI tools will be critical to their business’s success over the next two years. This figure increases to 81% amongst those already using AI tools (source: Connected Commerce Council)
• 63% of SMB leaders believe AI tools help “level the playing field” for businesses of all sizes, with 83% of those already using AI tools supporting this view (source: Connected Commerce Council)

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Written by Luke Budka, AI director at Definition

Updated on 05/06/2025