Using AI to automate repetitive tasks is nothing new, but generative AI opens up a new world of possibilities. Because of its ability to analyse large amounts of information and create new content, it's already revolutionising how businesses generate content, write code and design products. Generative AI-powered chatbots offer 24/7 customer support while other kinds of generative AI are hard at work researching the pharmaceuticals of the future and developing better clinical testing methods.
These generative AI use cases provide an overview of the impact of AI on everything from people in the workforce to specific industries already embracing this technology.
Within two months of its launch, ChatGPT had at least 100 million users, making it the fastest-growing app in history. As more businesses have rolled out competing chatbots and added generative AI to existing software, the number of people using AI has continued to grow. The statistics below are a snapshot of where generative AI is right now and where it's heading.
1. Only 16% of enterprises are using open-source generative AI models. (O'Reilly)
2. Over the last 12 months, more than 60% of new cloud/SaaS unicorns are generative AI native. (Accel)
3. IDC predicts the global AI market will be worth $521 billion by 2027. (IDC)
4. North America had 42% of the overall generative AI market share as of late 2023. (Market.us)
5. Within 10 years, generative AI could increase global GDP by as much as 7%. (Goldman Sachs)
6. For $1 companies are spending on AI, they are realising $3.50 in ROI. (IDC)
7. More than 80% of companies are planning on adopting generative AI by 2025. (World Economic Forum)
From analysing large data sets to designing new products and helping doctors diagnose patients, AI usage will only increase as the technology advances. In turn, consumer confidence will improve and create new users and applications.
8. AI is being woven into the workplace at an unexpected scale, with 75% of knowledge workers using AI in 2024, compared to 46% of users six months previous. (Microsoft)
9. By 2025, up to 30% of outbound marketing messages from large companies are expected to be generated by AI. (Gartner)
10. Detecting fraud, risk management and cybersecurity are three of the biggest benefits of AI, according to survey respondents. (MIT Technology Review)
11. Thirty-seven percent of marketing and advertising professionals have used generative AI at their jobs. (Fishbowl)
12. Nearly 50% of the most common use cases for generative AI are troubleshooting and technical assistance, professional and personal support, and education and learning. (Harvard Business Review)
Generative AI is everywhere in the news, but its adoption for business is uneven. While certain industries, including marketing and telecom companies, use the technology regularly, others are more cautious about responsible AI implementation as they try to find applications that save time and money while ensuring tools are ethical and safe.
AI-based cybersecurity helps to overcome roadblocks to adoption. Because of generative AI's ability to process huge amounts of data quickly and make changes when needed, these systems can be more secure much faster than they would be with only human assessment. With innovations like the ones found in the Now Platform's Tokyo release, including the ServiceNow Vault, data can be anonymised and protected to keep up with shifting compliance requirements and grow consumer trust.
14. One study in 2023 found that consumers lose trust in brands when they share information with AI. (International Journal of Research in Marketing)
15. Almost 30% of Gen X, Gen Z and millennials use AI at their jobs. (Fishbowl)
16. Around 3 in 4 employees across all age groups are using generative AI tools at work not provided by their organisations. (Microsoft)
17. More than a third of businesses cite accountability and ethics concerns as a reason for slower generative AI adoption. (EY)
18. Data analysis (59%) and AI programming skills (66%) are the most in-demand skills among AI users. (O'Reilly)
19. Marketing, technology, and consulting businesses are the industries with the highest rate of AI adoption. (Fishbowl)
Generative AI has a major impact on worker productivity, acting as a teammate, rather than a replacement, for the human workforce.
The rapidly changing technology highlights the need for upskilling and continuous education for knowledge workers, creatives, people in manufacturing and many other fields that are just starting to integrate AI.
20. A recent study suggests that 60% to 70% of work could be automated by AI, freeing up time for more innovation and strategic thinking. (McKinsey)
21. A survey found that 79% of CEOs said they want AI to help speed up innovation. (Deloitte)
22. Product development, data and AI, and sales jobs are expected to see the largest influx of workers from outside those current job families. (World Economic Forum)
23. Data-sharing, intelligence/analytics and data management are among the most important areas for generative AI use, according to one survey. (MIT Technology Review)
24. More than 12 million occupational shifts could occur by 2030 due to generative AI. (McKinsey)
25. 76% of workers say they need AI skills to remain competitive in the job market. (Microsoft)
26. 69% of workers say AI can help them get promoted faster, and 79% say AI skills will broaden job opportunities. (Microsoft)
27. 82% of leaders say their employees will need new skills to be prepared for the growth of AI. (Microsoft)
While nearly every industry will be impacted by AI, healthcare, software development and finance are near the top of the list with the highest potential for innovation, adoption and growth. From writing new code and solving complex coding issues faster to drastically reducing research costs for pharmaceuticals and creating better customer experiences, the benefits of these technologies could be world-changing.
Generative AI is set to revolutionise the way that software developers work. With many coding tasks able to be handled through AI code generation, coders and developers can focus their energy on other important tasks that can keep their projects on budget and on time.
28. Software developers using generative AI tools experienced a 25% to 30% improvement in their ability to complete complex coding under a deadline. (McKinsey)
29. Generative AI tools are used by 95% of devs writing code. (Sourcegraph)
30. A study of GitHub users found that developers using one generative AI program completed tasks 55% faster than users not using the program. (GitHub)
31. One report suggests that software developers can reduce the time it takes to write new code by as much as 50% using generative AI tools. (McKinsey)
Because healthcare is such a complex field, it can seem difficult to make changes, even if those changes would benefit patients, doctors and companies. Generative AI is poised to streamline data collection and organisation to make searching patient records faster, improve billing speeds and even help doctors and researchers find new drugs and make more accurate diagnoses.
32. One study found an almost 40% success rate in generative AI diagnosing difficult medical cases correctly. (Jama Network)
33. Generative AI may be responsible for discovering as much as 30% of new pharmaceutical drugs by 2025. (Gartner)
34. Fifty-three percent of hospitals and healthcare systems are incorporating generative AI into some of their systems. (Deloitte)
Finance has long positioned itself as a field willing to take on new technologies to make trading faster, more efficient and safer. Generative AI will continue to help financial businesses save time by automating more processes, identifying trends faster and helping these businesses stay compliant.
35. An analysis found that up to 40% of work could be automated with generative AI in fields like banking, software and insurance. (Accenture)
36. A study found that 34% of financial businesses are running pilot programs using generative AI to help detect fraud. (Capgemini Research Institute)
37. Large financial institutions use generative AI to learn about internal and legal regulations to maintain compliance and automate compliance checks. (McKinsey)
Maximising profits, reducing fraud and providing new levels of security are just three of the potential benefits of generative AI in the banking industry. Early forecasts show just how explosive the growth of the industry after using generative AI could be.
38. Investment by banks and other financial institutions could reach more than $100 billion by 2032. (Global Market Insights)
39. Banking may see a value add of $200 billion to $340 billion due to the effectiveness of generative AI. (McKinsey)
40. One study found that generative AI could augment as much as 34% of the work done by bank employees. (Accenture)
Because of the potential for almost limitless uses of generative AI, the financial impact could be massive. A large language model's ability to comprehend written language could greatly improve worker productivity and create higher profits. Take a look at a few statistics about the generative AI market size and its global financial impact.
41. The generative AI industry is projected to reach a market value of over $188 billion by 2032. (The Brainy Insights)
42. More than $12 billion of deals involving generative AI companies were generated in the first quarter of 2023. (PitchBook)
43. Generative AI's overall impact on the global economy could be as large as $15.7 trillion by 2030. (PwC)
44. Nearly two-thirds of CEOs say that creditors, investors and lenders are putting pressure on them to speed up generative AI usage. (IBM)
45. Organisations using AI experienced an 18% increase in customer satisfaction, employee productivity and market share. (IDC)
As new uses and better versions of generative AI come to market, the possibilities will continue to expand. If your business needs to reduce customer service costs, improve talent development or further automate processes, learn how ServiceNow can make it happen.
With generative AI built into the Now Platform, the power of machine learning and natural language processing is at your team's fingertips. The out-of-the-box solutions make it easier and faster to augment and automate processes without requiring expertise in data science.