Our team members Martin Reisenbichler, Malik Stromberg and Gabriela Izabela Makar presented new research on AI-driven disruption in marketing, Consumer behavior modeling via AI and Implications, limitations, and strategic consequences for brands and businesses.

The talk by Gabriela Makar “From Google to AI Search: the Battle for Visibility in the Age of Large Language Models” revealed key insights from ranking data (2019–2025), showing how AI favors large brands, increases content similarity, and reshapes digital competition. As AI search evolves, smart adaptation is critical. This is just the start of our ongoing research into the impact of large language models.

Malik Stromberg presented his research about ”Blind Spots in Broad Strokes: Caveats for the use of LLMs in Marketing Research” explains the question Can large language models (LLMs) reliably simulate consumer behavior?
New research shows that while LLMs can mirror human responses on brand tracking surveys at a high level, accuracy varies across the purchase funnel.
They perform well on awareness and recommendation but tend to overpredict at key decision stages like consideration and purchase—especially for popular brands. Adding demographic context helps, but limits remain as insights get more granular.
LLMs offer promise for scalable research—but precision still has its challenges.

Martin Reisenbichler hosted a special session "Generative AI in Marketing: Promise, Peril, and the Path Forward" on Friday, June 13, 2025 together with Daniel Ringel from UNC Kenan-Flagler Business School. The invited speakers were Alex Burnap from Yale School of Management, as well as Shane Wang from Virginia Tech.

From AI-enhanced digital twins for predicting customer behavior to AI generated advertisement and propaganda in political discourse, this session explores cutting-edge research on how generative AI is transforming marketing - highlighting both the breakthroughs and the ethical, environmental, and societal challenges.

Martin Reisenbichler presented his research, "From Pixel to Purchase: Engaging Customers with Visual Generative AI," highlighting the potential of AI in revolutionizing brand communication through visual advertising. The research demonstrates that fine-tuned AI models can generate visuals that outperform traditional ads in key areas like engagement, purchase intent, and brand perception. The study also explores AI's capacity to optimize multiple communication objectives and adapt to diverse audiences.
The presentation also acknowledged certain limitations, such as those related to brand familiarity and product category.