Unlocking Gen AI’s Potential – With AI at Wharton
By Jeremy Korst
I recently had the pleasure of joining Wharton’s AI Horizons webinar series with my co-authors, Professor Stefano Puntoni, Faculty Co-Director of AI at Wharton, and Mary Purk, formerly with AI at Wharton, to discuss our latest report, Growing Up: Navigating Gen AI’s Early Years. Together, we explored key findings from this year’s report compared to the initial 2023 study, and shared observations on the future of AI at work.
Based on a survey of 800 senior leaders from U.S. enterprises, our second annual study reveals not only how rapidly Gen AI adoption is accelerating but also offers some interesting year-over-year comparisons on adoption and level of investment by company size, industry and functional area, emerging applications and use cases, as well as overall business leaders’ sentiment on Gen AI.
Below are some of my thoughts and key takeaways from the discussion, along with the most interesting findings from our report for marketers as we look ahead to 2025.
GROWING UP: NAVIGATING GEN AI’S EARLY YEARS -> CLICK HERE TO GET THE FULL REPORT
From Wonderment to Widespread Use
In 2023, Gen AI was still in its early infancy with only 37% of company leaders using it weekly. This year, we saw much broader adoption with nearly three in four leaders (72%) using Gen AI weekly at work—with AI spending up 130% year over year.
This surge in adoption reflects not only curiosity, but an urgency to integrate Gen AI into workflows and use cases in ways that create real value. While 2024 primarily spanned trials and experimentation, we are now seeing an intense focus by enterprises on delivering tangible ROI with more practical use cases and applications.
“There is a sharp focus by business leaders on finding the ROI connection between the technology and what it produces in terms of outcomes.” - Mary Purk, formerly with AI at Wharton
As Mary Purk noted during our webinar, there is a sharp focus by business leaders “on finding the ROI connection between the technology and what it produces in terms of outcomes.”
This shift requires both a strategic and practical approach by marketers. Embedding AI effectively into processes requires investment, upskilling, and problem-solving. It’s not just about deciding to adopt AI—it’s about figuring out how to do it in a way that delivers results.
Marketing and Sales Leaders Embrace Gen AI
Perhaps the most notable finding from our report is the dramatic rise in Gen AI adoption among Marketing and Sales leaders. Nearly two-thirds (62%) of marketing leaders now use Gen AI multiple times per week, compared to just 20% in our initial report last year.
Stefano Puntoni observed that “marketing-related use cases are growing quickly. Content generation, personalized marketing, and customer insights are transforming the way marketers approach their work. These changes are profound and happening faster than we could have imagined.”
This shift highlights a fundamental change in how marketing departments view AI’s potential. It’s also a sharp contrast to our findings in 2023 that showed Marketing and Sales lagging behind all other departments, not only in adoption but also in their understanding of Gen AI. Only 21% of leaders in these functions had substantial knowledge of the technology, compared to HR (44%), purchasing (57%), product/engineering (60%), and IT (80%).
This difference among marketing and sales versus other function was so stark that Stefano and I wrote about it in Harvard Business Review last fall. Since then, marketers have gone from cautious observers to eager adopters, rapidly integrating Gen AI into their strategies and daily workflows.
"What's particularly interesting is how marketers are starting to use Gen AI not only for operational efficiency but as a strategic tool to uncover new opportunities and drive innovation,” said Stefano. “We're seeing a shift from simply automating tasks to reimagining what’s possible in marketing, from hyper-personalized customer experiences to entirely new ways of engaging with audiences."
“Marketing-related use cases are growing quickly. Content generation, personalized marketing, and customer insights are transforming the way marketers approach their work. These changes are profound and happening faster than we could have imagined.” - Wharton Prof. Stefano Puntoni
Spending Priorities Reflect a People-Centric Approach
This increased adoption in Gen AI is helping to drive a broader wave of investment: AI spending has surged by 130%, with 3 in 4 leaders planning additional investments in 2025. But in contrast to last year, these investments are no longer confined to technology alone.
But most of this investment isn’t going to the technology itself. Only about a third of Gen AI budgets are directed toward technology, with the majority spent on people and processes. Specifically, 20% of investment is being directed toward upskilling existing employees, another 20% to onboarding new hires, and 25% to consulting services for scaling AI effectively. This illustrates that we aren’t just in the midst of a technological change (e.g., the migration to cloud computing), but a more massive evolution for organizations.
“Companies are realizing that success with Gen AI isn’t just about having the right tools—it’s about empowering people to use them effectively,” said Stefano.
Leaders’ Optimism About Gen AI Continues to Grow
Our report also reveals a significant shift in how business leaders view Gen AI’s impact on employees. In 2024, 90% of respondents agreed that Gen AI enhances employee skills, up from 80% in 2023. At the same time, concerns about job replacement eased slightly, with fears dropping from 75% to 72%. This optimism reflects the collaborative potential of Gen AI.
“There’s been a clear shift in mindset,” Stefano shared during the webinar. “Leaders are increasingly viewing AI as a tool to augment employee capabilities rather than replace them, with a focus on enhancing productivity and improving work quality.”
For marketers, the tools are amplifying creativity—helping teams streamline execution, analyze data more quickly, and generate new insights and ideas. As firms continue to integrate Gen AI into workflows, we’ll continue to see it reshape the way teams collaborate and deliver results.
Putting Your Strategy First
As marketers move beyond experimentation to broader use, it’s critical to view Gen AI as a tool, not a strategy. The focus should be on cutting through vendor hype to discover AI solutions that genuinely enhance brand value and deepen customer connections.
Beyond investment, scaling Gen AI effectively calls for a holistic strategy that empowers marketing and other departments to fully leverage its potential. This involves not only integrating the technology but also fostering a cultural shift across the organization to ensure its success.
Achieving this balance is key. Successfully applying Gen AI requires both a top-down vision—where leaders set the direction—and a lot of bottom-up energy, where individual employees discover how it can help them in their roles.
Teams are not only using Gen AI to innovate faster and streamline workflows but also to simplify complex tasks like visualizing data, generating reports, and summarizing unstructured data. There are some limitations, though. While I use generative AI as a quick testing ground to fine-tune language or summarize data, the tool is not at a point where it can replace the value provided by humans.
Another challenge with AI-generated insights is the need to separate the signal from the noise. The last thing companies want to create is more information silos with different insights being applied by different teams with no clear oversight.
"The key to making good decisions with data is to think without data,” says Stefano. “For marketers, this means dedicating resources to not only adopt AI tools but to ensure teams have the skills and confidence to use them creatively and strategically.”
About Half of Enterprises Have Few or No Restrictions on Gen AI Usage
Another interesting finding from our report is that approximately half of the companies surveyed reported having few or no restrictions on how Gen AI is used.
This openness allows for more experimentation, especially in areas like marketing, where teams are exploring novel applications to personalize, optimize customer engagement, and create content at scale. However, with freedom comes risk, with AI co-pilots often creating unintended access to sensitive data.
Data security and employee permissions are becoming a major focus. While enterprise-grade AI platforms have addressed many privacy concerns, internal governance remains a significant challenge for scaling adoption.
“Larger organizations face challenges with Gen AI adoption due to security and data access, as well as concerns about implementing the technology without the right controls,” said Mary. “I often encourage these companies to observe smaller, more agile competitors who are further along the experimentation curve. Larger companies can learn from these examples, not to copy them outright, but to consider how such experimentation might apply to their own strategies.”
Ultimately, companies need clear guardrails for Gen AI use: securing customer data, ensuring appropriate employee and AI access, and aligning AI initiatives with broader strategic goals. Ensuring that these priorities are met will help drive measurable ROI while preserving trust and brand integrity. Relatedly, Gartner analyst Max Goss reported that 40% of Microsoft CoPilot deployments have been delayed by at least 3 months due to findings and concerns around data governance and unintended employee access.
“Openness allows for more experimentation. However, with freedom comes risk, with AI co-pilots often creating unintended access to sensitive data.” - GBK Partner Jeremy Korst
Recommendations for Marketing and Sales Leaders:
So how should marketing and sales leaders apply Gen AI going forward? The current environment provides ample opportunity for marketing leaders to establish at least near-term advantage over their competitors by identifying ways their teams can effectively use Gen AI. Their success will hinge on clear understanding, conscious experimentation, and careful consideration of both risks and rewards.
To guide your efforts, start by asking these critical questions:
1. Is your data AI-ready? Data is the lifeblood of AI. High-quality, well-organized data is essential for generating accurate and actionable insights.
2. Do you have a well-defined approach to data governance and employee access across teams and functional areas? Establishing clarity and consistency in how data is managed—and who can access it— ensures it supports AI applications effectively. Safeguarding customer and proprietary data is paramount, as is ensuring your company avoids unintended access to sensitive data through AI co-pilots. Gen AI has an uncanny ability to find and unveil sensitive data if adequate controls aren’t in place.
3. How do you balance bottom-up experimentation with oversight? Experimentation is key, but it must be accompanied by a top-down strategy and policies to maintain compliance, protect data, and drive organizational alignment, while also removing information silos.
4. How are we measuring outcomes and ROI? Clear success metrics are necessary to demonstrate Gen AI’s value and ensure alignment with broader business goals, especially as enterprises transition from experimentation to tangible outcomes.
5. Does your Gen AI plan adequately account for people, process and technology? Organizations are finding that investing in technology is just part of the equation. Adequate investments in team member training and establishing new ways of working are needed to effectively drive adoption.
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.