Forget The Hype. Here’s What Enterprises Are Actually Doing with Generative AI
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By Jeremy Korst
I recently had the pleasure of joining for the Punk CX podcast hosted by Forbes columnist Adrian Swinscoe, along with GBK advisor Dr. Stefano Puntoni, Professor of Marketing at The Wharton School and Faculty Co-Director of AI at Wharton, to discuss the results of our study on “The Rise of Generative AI Across Enterprises”.
Among the questions we explored in the episode: what are the biggest use cases and emerging applications for generative AI? How will it affect the future of work? What are the biggest concerns or barriers to adoption? And finally, what guardrails should leaders put in place as they apply generative AI with their teams?
In this blog post, I share some key takeaways from the report, our podcast discussion with Adrian, as well as a recent HBR article that Professor Puntoni and I co-wrote based on our study.
THE RISE OF GENERATIVE AI ACROSS ENTERPRISES -> CLICK HERE TO GET THE FULL REPORT
The rise of generative AI
One of the big eye-openers from GBK’s study, based on a survey with 672 senior leaders from U.S. enterprises, each with annual sales surpassing $50 million, is just how rapid the adoption of generative AI already is. More than half (58%) of enterprise leaders now use generative AI tools at work and that percentage continues to grow as teams integrate it into their workflow.
“Our report provides a good snapshot of the current state of play,” said Professor Puntoni. “To me one of the big eye openers was just how far and deep adoption for generative AI already is. This is not a technology that is around the corner. This is something that is already percolating quite deep into the work practice of many, many people.”
“To me, one of the big eye-openers was just how far and deep adoption for generative AI already is. This is not a technology that is around the corner. It’s already here.”
- Wharton Professor Stefano Puntoni
In our study, we also asked senior leaders to share their perspective on the biggest applications or emerging use cases for generative AI. Across the board, leaders across functional areas agree that generative AI will be broadly used for a wide range of applications including data analysis (89%), marketing content and creation (text, images, video) (87%), researching customer and competitive insights (84%), among others. The use of generative AI in software development, particularly coding, was also cited as a top use case.
As Prof. Puntoni notes, “upwards of 80% of respondents told us that their company is pursuing or plans to pursue a range of applications for generative AI in short order. This is not just some companies thinking of doing it – it's almost every company.”
What were the biggest surprises from the study?
There were some notable differences among leaders who reported using AI at work. One was around company size, with leaders in smaller companies (>$50 million in revenue) reporting more frequent usage than those in large companies.
Our study also showed a surprising knowledge gap with generative AI among sales and marketing leaders. While 80% of IT leaders note they have substantial knowledge about generative AI, only 21% of Sales and Marketing leaders did the same, trailing even Operations (26%), HR (44%), and Purchasing (57%). Marketing and sales leaders also reported the lowest utilization of generative AI for work-related tasks, with just 35% using it at work.
We also saw perceptions vary based on how often leaders had used the technology. Those who were heavily using generative AI (for example, IT, purchasing, and procurement) tended to be the most optimistic and excited about what it can do, whereas those who were using it infrequently (marketing and sales, operations) were among the most cautious.
What reservations do leaders have around generative AI?
Overall, 3 in 4 leaders said that they have a generally positive outlook on generative AI, but caution remains, particularly among those who use the technology less frequently. Leaders also hold mixed views on the impact of generative AI on human talent – with 48% saying it will enhance employee skills vs. replace them (36%). The majority of leaders (55%) also believe AI will improve work quality.
The primary motivators for adopting generative AI include boosting employee efficiency, optimizing business operations, enhancing employee creativity, developing new products and services, and reaching new audiences or markets. Conversely, concerns around inaccurate results, customer data privacy, internal pushback, ethical issues, and cost are the top barriers to adoption.
“While optimism about generative AI is prevalent, concerns around accuracy, bias, and AI's role in decision-making remain,” shares Prof. Puntoni. “Additionally, there's an underlying psychological concern by leaders around job replacement, especially among those who have yet to use the technology.”
Are marketers truly ready to maximize AI’s potential?
While the lower familiarity of marketing and sales leaders with generative AI is concerning, our study also showed they had the most curious about the technology (63%) of their functional peers, but this curiosity was tempered with a degree of skepticism with 2 in 3 marketing leaders describing their outlook on generative AI as cautious.
A notable 78% of leaders in marketing and sales acknowledged that generative AI would likely have some impact on their company. They identified enhanced effectiveness, employee efficiency, and improved customer experience as key potential benefits.
As Professor Puntoni summarizes “I think for a lot of marketers, generative AI is potentially a threatening technology. A big part of marketing is about content creation of some sort, whether it's creating advertising, social media posts, email campaigns, support materials for salespersons or whatever. A lot of the use cases that ranked highest in our survey are marketing related. You also have data analysis obviously relevant to market research.”
What safeguards should brands be putting in place to safely realize the potential of AI with customers?
The arrival of generative AI is exciting, with investment and applications expanding rapidly, but not all approaches are created equal. In our HBR article, and on the Punk CX podcast, Stefano and I shared several steps marketing and sales leaders can take to effectively leverage the potential of new generative AI systems:
1. Invest in training. This will enable teams to use and interpret generative AI output and recognize when human input is vital. In conducting training, work to develop an understanding of both the potential capabilities and shortcomings.
2. Embrace an intentional test-and-learn approach. This will help you pinpoint where generative AI could most efficiently improve tasks, content, and overall customer experience. In times of constrained budgets, this kind of targeted experimentation will enable teams to concentrate on higher-value tasks.
3. Establish policies to safeguard customer and proprietary company data. Until there are widespread generative AI solutions that ensure data protection, it’s prudent to treat all inputs and outputs as public domain.
4. Ensure quality control. Generative AI, while revolutionary, can and does produce errors, biases, and what are often referred to as “hallucinations.” It is imperative that marketing and sales leaders put into place robust quality-control and oversight mechanisms. This vigilance can mitigate potential risks of misinformation or bias, preserving the integrity of both the technology and the brand it serves.
5. Enhance creativity, don’t replace it. Generative AI isn’t just a tool that automates tasks. It’s also a capable co-pilot that helps leaders expand their thinking and develop new ideas. As its role grows, its most valuable impacts will come from enhancing, not replacing, human skills — boosting productivity and freeing us for tasks requiring our judgement, emotional intelligence, or other complex decision-making.
Why this all matters
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 shares, “Generative AI should not be seen as an excuse for thinking less. In fact, I think we need to think even harder. The more advanced the technology you’re working with, the more careful you need to be, the more deliberate, strategic, and thoughtful you ought to be.”
This resonates with a lot of conversations the team at GBK has had with senior executives in major companies – both in the way gen AI is going to improve the work functions for certain groups within the organization, taking more routine tasks off their plate to let them focus on more interesting work, while also investing in upskilling their workforce to be able to use AI effectively in their job.
Stefano's parting advice from the podcast is an important reminder: "Understand your customer. There’s a lot of emphasis on technology and the capabilities of systems and new algorithms. But they are nothing unless I serve the customer.”
My advice: Take an outside-in perspective. Even the world’s largest brands can’t be everything to everybody. And yet despite this, thousands of businesses launch new products and services every year with very little external market or customer insight. I see this same trend repeating with generative AI. While many tech companies claim to be “customer-centric,” in reality, they haven’t taken time to understand the group of consumers they are trying to serve and what makes them different.
As brands deploy user experiences based on AI, they need to make sure they are crafting that entire journey around the needs of their target customers.
Looking for more insights on emerging trends with generative AI and how you can maximize impact for your business? Click here to get a copy of our full report.