The Cambridge University Botanic Garden GenAI chatbots let visitors “talk” to plants in a live museum experiment.

The Cambridge University Botanic Garden has launched a GenAI exhibition called “Talking Plants.” Visitors scan QR codes to interact with 20 plant-based AI chatbots. Each chatbot represents a specific species in the garden’s collection. The system generates unique, real-time responses to visitor questions. Conversations adapt to user curiosity, pace, and language preference.

The challenge was scaling expert knowledge without overwhelming staff. Botanical expertise is deep but not always accessible on demand. Traditional signage limits personalization and multilingual engagement. GenAI addresses this gap through tailored dialogue grounded in curated botanical data. Each model reflects species biology, ecology, and conservation history. Engineers shaped distinct personalities while maintaining factual alignment with staff research.

The benefits extend beyond novelty. Visitors receive interactive, contextual explanations instead of static descriptions. The system enables self-directed learning and higher engagement among younger audiences. Importantly, the Garden frames the project as a supervised experiment. Human experts curate source material and monitor accuracy and environmental impact. The AI augments educators rather than replacing them.

Why it matters
GenAI is moving into public knowledge institutions as an engagement layer.
• Demonstrates how LLMs can scale domain expertise without scaling headcount
• Tests retrieval-grounded, personality-driven AI in cultural environments
• Represents enterprise experimentation with AI under governance and transparency

This case reflects a broader enterprise challenge: democratizing expert knowledge at scale. Museums, universities, and cultural institutions struggle to deliver personalized education affordably. GenAI offers a structured, multilingual interface to institutional knowledge. For AI practitioners, it signals the rise of curated, domain-specific conversational systems. The experiment also surfaces governance questions around ethics, sustainability, and trust. As AI reshapes search and discovery, structured, extractable knowledge becomes institutional infrastructure.