Here are the statistics from the report:
- Small enterprises (revenues between $50M-$200M) lead in frequent generative AI usage (57% at least once per week).
- Smaller firms ($50M-$200M) are prioritizing generative AI for sales content (91%), while mid-sized companies ($250M-$2B) focus on email generation and internal support (86%).
- 37% of enterprise leaders actively use generative AI weekly, and another 21% use it less frequently.
- 81% of leaders have an internal team of 10 or more focused exclusively on generative AI strategy.
- Technology industry leaders frequently utilizing generative AI at 60%, followed by Industrial/Construction at 43%, and Finance at 39%.
- Retail and Manufacturing have less frequent engagement with generative AI, at 26% and 36% respectively.
- Three in four enterprise leaders have a generally positive outlook on generative AI.
- 48% of senior leaders using the technology believe generative AI will enhance employee skills, while 36% believe it will replace them.
- 55% strongly agree that AI will enable higher quality work with the same number of employees, versus 43% who strongly agree it can achieve this with fewer employees.
- Investment in generative AI is expected to increase by 25% in the next 12 months, with firms exceeding $2B in revenue planning a 28% uptick.
- Retail and Professional Services industries anticipate the highest investment increases, with projected growth rates of 27% and 28% respectively.
- In the next 3-5 years, generative AI is expected to be broadly used for data analysis (89%), marketing content creation (87%), and researching customer & competitive insights (84%).
- Other anticipated applications include document editing and summarization (84%), customer support or internal help desk functions (82%), and automated email generation (82%).
- Less popular uses for generative AI are legal contracts (57%), recruitment (67%), and supply chain management (71%).
- Primary motivators for adopting generative AI include boosting employee efficiency, optimizing operations, enhancing creativity, developing new products/services, and reaching new audiences or markets.
- Top barriers to adoption include concerns about inaccurate results, customer privacy, internal pushback, ethical issues, and cost.
Stefano Puntoni, Director of AI at Wharton, contributed to the study with GBK: https://ai.wharton.upenn.edu/updates/generative-ai-hits-the-mainstream-majority-of-enterprise-leaders-adopt-and-plan-increased-investments-next-year/