Last year was a wild ride for anyone who follows the development of large language models (LLMs) and generative AI (GenAI). AI developers created GenAI applications that ranged from the experimental to the transformative, pushing the boundaries of what we know about the technology, how it works, and how it can be used to significantly change the world as we know it.
Let’s start with wild and make our way to enterprising.
The Wildest GenAI Use Case of 2024
In summer 2024, research lab Upward Spiral connected two instances of Anthropic’s Claude, dubbed the experiment Truth Terminal, and invited the LLMs to have a conversation. The result was astonishing: As the LLMs engaged in non-stop conversation, they fully explored the latent space of their training data in a way that no human has the time or capacity to do alone.
Those conversations are called The Infinite Backrooms, and you can view them today. When American businessman and software engineer Marc Andreessen heard about the experiment, he gave the models $50,000 in bitcoin to use in whatever way they might. And use it they did: The Infinite Backrooms launched a meme crypto coin they called Goatseus Maximus which, at the time of publishing this article, trades at a price of USD $0.12 per “GOAT” — with a 24-hour trading volume of nearly $25 million.
Dataiku GenAI Use Cases for the Enterprise
Not all experiments are as audacious or as lasting as Truth Terminal but they underscore the potential — and the risks — of GenAI for people and organizations. At Dataiku, we have worked with our customers to deliver more than 1,000 GenAI use cases. And during that time, we have seen patterns emerge.
In 2024, one of those patterns became demonstrably clear: applying GenAI to provide enterprise teams with up-to-the minute information and insights can transform business operations. For us, these three enterprise use cases in 2024 showcased how organizations could turn GenAI's promise into practical value for their operations.
1. Enhanced Customer Intelligence Through Review Analysis
For businesses with thousands of customer touchpoints, making sense of feedback at scale has always been challenging. Whataburger, a U.S.-based restaurant chain with over 1,000 locations, faced this challenge head-on with its customer review analysis.
With over 10,000 new online reviews coming in weekly and a total exceeding 15 million, Whataburger needed a more sophisticated approach than their traditional bag-of-words sentiment analysis. By implementing GenAI through Dataiku, they achieved remarkable results:
- Nearly doubled their topic discovery, uncovering 280,000 review topics compared to the previous 144,000
- Doubled model performance in sentiment analysis accuracy
- Enabled no-code analysis accessible to business users
- Gained ability to adjust review categories simply by modifying prompts, without pipeline changes
This enhancement in customer insight capabilities enables Whataburger to respond more effectively to customer feedback and identify improvement opportunities across their extensive operation.
2. Strategic Market Intelligence Automation
In the rapidly evolving energy sector, staying informed of market developments is crucial for executive decision-making. Ørsted, the global leader in offshore wind power, transformed their market intelligence process using GenAI to create an automated news digest system.
The impact was immediate and substantial:
- Saved 100 hours of employee time monthly, previously spent on generating manual summaries
- Attracted 500 internal subscribers within the first week of launch
- Automated processing of 300-500 daily industry articles
- Created two tailored daily digests: an executive summary of top 10 articles and a comprehensive 360° edition with up to 50 articles
This initiative not only improved efficiency but also ensured consistent market intelligence delivery across the organization, supporting Ørsted's mission to power the world with green energy.
3. Enterprise Knowledge Management
A leading global fashion retailer demonstrated how GenAI can transform internal knowledge sharing by deploying a custom chatbot to 16,000 employees worldwide. This implementation stands out for several reasons:
- Comprehensive deployment across headquarters and frontline store workers
- Cost-effective scaling compared to per-user licensed alternatives
- Flexible technical architecture allowing for capability expansion
- Enhanced knowledge access for both corporate and retail staff
The retailer used Dataiku to develop the solution, which provided immediate answers to common questions while maintaining the flexibility to expand capabilities as needs evolved.
Looking Ahead
As these examples demonstrate, GenAI is still in its early stages of adoption. Developers are testing its limits and organizations are applying it to deliver measurable business value across diverse industries. As with most technologies, the key to success lies not just in selecting the right use case but in implementing them thoughtfully with the right platform and approach.
Organizations leading in GenAI adoption share these common characteristics:
- Clear focus on measurable business outcomes
- Strong foundation in data management and governance
- Commitment to democratizing AI access across the organization
- Platform approach that enables scaling and iteration
In 2025, we expect to see more organizations moving from experimentation to full-scale deployment, learning from developers’ experiments and from early adopters who have already proven the value of enterprise GenAI implementations. Based on research published in our 2025 trends report, we also expect AI agents, which connect data, LLMs, and other technologies, to take center stage and showcase more fully the power and potential of GenAI.