The Rise of Generative AI Across Enterprises: Insights from GBK’s New Report with Dr. Stefano Puntoni, Director of AI at Wharton

Credit: Shutterstock

By GBK Collective

Today GBK is excited to announce the release of our latest report, The Rise of Generative AI in the Enterprise, directed by AI expert Dr. Stefano Puntoni, Sebastian S. Kresge Professor of Marketing at The Wharton School and Faculty Co-Director of AI at Wharton, and Jeremy Korst, former technology executive at Microsoft and T-Mobile and now President of GBK. Dan Ives, Managing Director of Equities Research at Wedbush Securities, also collaborated on the report. 

The report is based on a survey with 672 senior leaders from U.S. enterprises, each with annual sales surpassing $50 million, and shows generative AI adoption has reached a tipping point. Not only do the majority of enterprise leaders say they have used generative AI at work, leaders across functional areas are also making substantial increases to their investment in generative AI. 

"The results of our study show that we’ve passed a critical tipping point with generative AI,” said Prof. Puntoni. “This isn’t another metaverse. Enterprise decision makers across industries are adopting generative AI in droves and the wave is only going to grow, with investment spending set to surge by more than 25% in the next 12 months.” 

Our survey set out to answer several key questions. Where are large companies in their generative AI adoption journey? How is Gen AI being leveraged across different departments and industries? What impact will it have on employees now and in the future? What are the key factors driving its implementation? And finally, what brands are leading the way?  

 THE RISE OF GENERATIVE AI ACROSS ENTERPRISES -> CLICK HERE TO GET THE FULL REPORT  

“Generative AI has passed a critical tipping point. This isn’t another metaverse. Enterprise leaders across industries are adopting in droves and the wave is only going to grow.” - Prof. Stefano Puntoni, Co-Director of AI at Wharton

Generative AI Usage: Industry and Company Size:   

 The results are eye-opening. Not only are senior leaders across industries embracing generative AI, 37% of leaders actively use it weekly with another 21% using it less frequently. Additionally, 8 out of 10 leaders (81%) confirm having an internal team of 10 or more focused exclusively on generative AI strategy.  

“We were stunned by many of the findings, including the number of business leaders already using generative AI in their work and the widespread use cases” note Prof. Puntoni. “This is not a technology that's ‘around the corner’. It's already here.” 

When it comes to the frequency of usage based on company size, smaller enterprises (with revenues ranging from $50M-$250M) are leading, with 57% tapping into generative AI at least weekly. In contrast, larger firms, especially those surpassing $2B in revenue, exhibit a notable potential for more intensive AI engagement, especially in sectors like Retail and Manufacturing. 

By industry, not surprisingly Technology is at the forefront, with 60% of tech leaders making frequent use of generative AI, followed by Industrial/Construction and Finance at 43% and 39%, respectively. In contrast, just 26% of leaders in Retail and 36% in Professional Services and Manufacturing engage with generative AI routinely.  

“Our study not only shows rapid adoption of generative AI, but varying levels of maturity,” said Korst. “Some organizations are still in the exploratory phase, while others have seamlessly incorporated generative AI into their daily workflow. We also see significant differences in usage, overall knowledge, and skills related to generative AI by industry and department.”  

Triggers and Barriers to Generative AI Adoption  

Three in four enterprise leaders have a generally positive outlook toward generative AI according to our survey. That being said, nearly all respondents expressed caution, particularly among those who use the technology less frequently.  

The primary motivators for adopting generative AI include boosting employee efficiency, optimizing business operations, enhancing employee creativity, development of new products and services, and reaching new audiences or markets.  

“What is innovation? Typically, we define it as new and useful. Now, with generative AI, the cost of 'new' has gone to zero. Yet, the cost of 'useful' remains. We're transitioning from being artists to art critics. From creators to curators who discern where the real value lies.” - Prof. Stefano Puntoni

Conversely, concerns around inaccurate results, customer privacy, internal pushback, ethical issues and cost are the top barriers to adoption. Companies with $50M-$250M in revenue worry most about data confidentiality, with accuracy being the top concern cited by firms with revenue of $2B+ annually.  

“While optimism about generative AI is prevalent, concerns around accuracy, bias, and AI's role in decision-making remain,” shared Prof. Puntoni. “Additionally, there's an underlying psychological concern by leaders around job replacement, especially among those who have yet to use the technology. As generative AI becomes increasingly ingrained across teams, striking the right balance with AI governance and employee education will be pivotal.”

Will Generative AI Replace or Augment Human Talent?  

 For the moment, our study shows that generative AI is seen as more helpful than harmful to employees. Senior leaders currently using the technology are more likely to state that generative AI will enhance employee skills versus replace them (48% vs. 36% strongly agree).   

Moreover, most enterprise leaders don’t believe the technology can completely substitute human talent. It can, however, improve work quality (55% strongly agree that AI will enable higher quality with the same employees vs. 43% who strongly agree but with fewer employees).   

“Generative AI, while revolutionary, is not immune to errors,” said Korst. “It's crucial for leaders to have strong quality control mechanisms in place to monitor and validate AI-generated output from data analysis to content. This not only ensures accuracy but helps to mitigate risks and maintain the integrity of the brand."  

Investments in Generative AI Poised to Surge  

 Despite the risks and challenges, investment in generative AI is on track for significant growth with companies across industries planning to increase investments by 25% in the next 12 months led by firms with revenues exceeding $2B (which plan a 28% uptick in spend). Industries currently lagging in generative AI adoption, such as Retail and Professional Services, anticipate the most significant investment increases, with projected growth rates of 27% and 28%, respectively.  

Emerging Applications and Use Cases  

“Use cases for generative AI continue to explode with enterprises across industries now viewing AI as a major strategic initiative in the coming years," commented Dan Ives, Managing Director at Wedbush Securities and a collaborator on the report. “We continue to view AI as the most transformational tech trend since the birth of the Internet in 1995." 

When asked what use cases and applications would be most prominent for generative AI, enterprise leaders overwhelmingly point to a future where these AI models become indispensable co-pilots in the workplace. In the next 3-5 years, decision-makers across the board agree that generative AI will be broadly used for generating data analysis (89%), marketing content and creation (text, images, video) (87%), as well as researching customer & competitive insights (84%).  

Other top applications include document editing and summarization (84%), customer support (82%), and automated email generation (82%). Among the use cases we tested, the least popular for generative AI are expected to be legal contracts (57%), recruitment (67%), and supply chain management (71%), although these percentages are still notably high.   

“We continue to view AI as the most transformational tech trend since the birth of the Internet in 1995.” - Dan Ives, Managing Director at Wedbush Securities

The Future of Generative AI 

Our report shows a dynamic future for generative AI, with investment and applications expanding rapidly, but as Prof. Puntoni notes “not all approaches are created equal. While AI can analyze mountains of data in seconds, human oversight and asking the right questions is vital to ensure accurate and responsible use of AI-generated outputs.” 

This comment underscores the transformative shift and evolution businesses will undergo over the next several years. Ultimately every role across enterprises has the potential to be impacted by generative AI, as humans working with AI co-pilots becomes the norm, dramatically amplifying what people can achieve. 

As we break down jobs into automatable tasks or those needing AI assistance – from data analysis and coding to content creation and document editing – we're rapidly progressing toward a future defined by seamless human and machine collaboration. But in this new world, quality control and human oversight is more important than ever. 

As Prof. Puntoni succinctly sums up: “One way to think about the future impact of generative AI is to ask what is innovation? Typically, we define it as new and useful. Now, with generative AI, the cost of 'new' has gone to zero. Yet, the cost of 'useful' remains. We're transitioning from being artists to art critics. From creators to curators who discern where the real value lies.” 

Looking for more insights on emerging trends with generative AI and how you can maximize impact for your business? Click here to get a complimentary copy of our full report. 

 

Share this article

 

Follow us and stay up to date

Previous
Previous

What Is the Future of AI?

Next
Next

The Rise of Generative AI Across Enterprises