Published by Seb Murray with permission from Knowledge@Wharton, Wharton's online business journal.
Since the launch of OpenAI’s ChatGPT chatbot in November last year, there has been a wave of ground-breaking generative AI launches. Companies like Microsoft are developing new AI tools, providing productivity-enhancing software that potentially empowers millions of workers to automate tasks like document and email generation or spreadsheet creation.
In a new study carried out in collaboration with marketing consultancy GBK Collective, Wharton marketing professor Stefano Puntoni unearthed fresh insights into the adoption of generative AI and its impact across the U.S. economy. He said that generative AI is relatively new, and no blueprint or recipe exists for its implementation. “Everybody is experimenting, the technology is changing very fast. This paper helps us understand the state of play,” he explained.
U.S. Survey Shows Generative AI Is Here to Stay
Puntoni’s research revealed that generative AI has reached a critical threshold, experiencing significant and rapid adoption, leading to substantial changes in business practices. He polled 672 respondents based in the U.S. “Over 50% of the sample is already using generative AI in their work, with many use cases indicated as being already under exploration or soon to be. This shows the tech has already passed a crucial tipping point,” he said.
Furthermore, the study predicts that the situation is unlikely to reverse anytime soon. In the next 12 months, enterprises plan to increase their spending on generative AI by an additional 25%. Much of this spending will be allocated to internal teams that are tasked with developing generative AI strategies.
However, the research also suggests that external partners will play a significant role, with half of the businesses surveyed expecting to bring in external consultants, partners, or contractors. “I expect we’ll see very fast-growing lines of businesses for the main consulting and IT outsourcing companies,” Puntoni said.
What Industries Benefit Most From Generative AI Investments?
The study highlights how the most significant growth in generative AI investment will occur in sectors and functions where current adoption is still in its nascent stages. This includes larger corporations, the professional services and retail industries, as well as marketing, sales, HR, and operations departments.
Smaller companies are more agile in leveraging the potential of generative AI compared to their larger counterparts (57% vs. 18%). This reflects their ability to adapt tools and processes quickly, driven by the greater pressure to realize the efficiency gains of generative AI. “The technology can streamline processes and reduce operational costs, potentially giving smaller firms a competitive edge,” explained Puntoni.
Will Generative AI Investments Impact Jobs? Executives Are Mostly Optimistic
Despite the anticipated surge in generative AI investments, the executives surveyed are optimistic that generative AI will not lead to widespread job cuts. Rather, they believe it will enhance employee skills in some tasks (48% of those using AI said this) rather than replace human skills (36%). “At the end of the day, generative AI is producing content — that’s what many office workers are doing. On the other hand, this will be a way for existing employees to do a much better job, or more jobs. Which scenario — skill enhancement or replacement — prevails will depend on the function, company, and specific employees,” Puntoni said.
Business leaders polled in the survey anticipate a wide array of tasks that generative AI will undertake in the coming years, with a strong focus on data analysis (89% cited this task), marketing content creation (87%), and customer and competitor research (84%). The use of generative AI in software development, particularly coding, also receives high endorsements. “The quip now is that the hottest programming language is English — you can just tell the algorithm what you want it to code,” said Puntoni.
The majority of those surveyed believe that generative AI will be used for managing supply chains (71%) and recruiting employees (67%). However, a smaller proportion (58%) expects AI to assist in drafting legal contracts, possibly due to concerns regarding accuracy.
Nevertheless, the study demonstrates that generative AI will deliver substantial benefits to businesses, with executives expecting enhanced employee efficiency and optimized business operations. “A lot of companies can use this technology not just to cut costs but to help employees do a better job. Those who believe the tech is powerful think it will raise both efficiency and effectiveness,” Puntoni stated.
Businesses Continue to Wrestle With Pros and Cons of AI
However, the research shines a spotlight on the challenges that executives face when implementing generative AI into their businesses. Key concerns revolve around the accuracy of results (AI has been known to produce “hallucinations”), the risk to customer privacy, internal resistance, and ethical considerations. Decision-makers express a range of emotions about AI, including caution (reported by 64% of those who don’t yet use generative AI) and skepticism (35%).
“Concerns revolve around privacy and data: to what extent can we use these algorithms when we’re feeding them with data we might not want to be outside the company?” noted Puntoni. However, these concerns are balanced by feelings of optimism (expressed by 62% of AI-users) and excitement (55%) about AI’s potential.
Key Recommendations for Leaders Using Generative AI
For those looking to harness the positive benefits of generative AI, Puntoni offered three key recommendations. Firstly, he stressed the importance of embracing an intentional “test and learn approach,” ensuring there is a method in the madness. “Leaders should maximize organizational learning while minimizing risks and share the new insights with others,” he said.
Secondly, companies should establish policies for dealing with company and customer data. “They must ensure technical and legal support in the intentional testing and learning approach, incorporate quality-control systems — especially for front-line service deployment — and invest in training for staff,” Puntoni said.
Lastly, he advocates for using generative AI to make humans more productive and capable rather than seeking to make them obsolete. “Far from the doomsday scenarios we often read in the media, generative AI offers organizations the opportunity to help many employees find more meaning in their work and creativity, fostering human flourishing,” concluded Puntoni.