# The Impact of Generative Artificial Intelligence on Ideation and the performance of Innovation Teams (Preprint)

arXiv: https://arxiv.org/abs/2410.18357 · HTML: https://mlsanity.com/paper/2410.18357/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 13 of its 98 references that are in the map.
- First posted on arXiv 23 Sep 2024.

## Builds on (most cited first, 13 of 13)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Language Models are Few-Shot Learners](https://mlsanity.com/paper/2005.14165/) (2020)
- [Emergent Abilities of Large Language Models](https://mlsanity.com/paper/2206.07682/) (2022)
- [Language Models as Knowledge Bases?](https://mlsanity.com/paper/1909.01066/) (2019)
- [A Primer in BERTology: What we know about how BERT works](https://mlsanity.com/paper/2002.12327/) (2020)
- [COMET: Commonsense Transformers for Automatic Knowledge Graph Construction](https://mlsanity.com/paper/1906.05317/) (2019)
- [The Impact of AI on Developer Productivity: Evidence from GitHub Copilot](https://mlsanity.com/paper/2302.06590/) (2023)
- [Symbolic Knowledge Distillation: from General Language Models to Commonsense Models](https://mlsanity.com/paper/2110.07178/) (2021)
- [Can Large Language Models Explain Themselves? A Study of LLM-Generated Self-Explanations](https://mlsanity.com/paper/2310.11207/) (2023)
- [AI-Augmented Brainwriting: Investigating the use of LLMs in group ideation](https://mlsanity.com/paper/2402.14978/) (2024)
- [Analyzing Commonsense Emergence in Few-shot Knowledge Models](https://mlsanity.com/paper/2101.00297/) (2021)
- [Relational World Knowledge Representation in Contextual Language Models: A Review](https://mlsanity.com/paper/2104.05837/) (2021)
- [BertNet: Harvesting Knowledge Graphs with Arbitrary Relations from Pretrained Language Models](https://mlsanity.com/paper/2206.14268/) (2022)

## Built on by (most cited first, 3 of 3)

- [Vibe Coding as a Reconfiguration of Intent Mediation in Software Development: Definition, Implications, and Research Agenda](https://mlsanity.com/paper/2507.21928/) (2025)
- [GAI: Generative Agents for Innovation](https://mlsanity.com/paper/2412.18899/) (2024)
- [The Ghost in the Keys: A Disklavier Demo for Human-AI Musical Co-Creativity](https://mlsanity.com/paper/2511.01663/) (2025)

## Abstract (arXiv)

This study investigates the impact of Generative Artificial Intelligence (GenAI) on the dynamics and performance of innovation teams during the idea generation phase of the innovation process. Utilizing a custom AI-augmented ideation tool, the study applies the Knowledge Spillover Theory of Entrepreneurship to understand the effects of AI on knowledge spillover, generation and application. Through a framed field experiment with participants divided into experimental and control groups, findings indicate that AI-augmented teams generated higher quality ideas in less time. GenAI application led to improved efficiency, knowledge exchange, increased satisfaction and engagement as well as enhanced idea diversity. These results highlight the transformative role of the field of AI within the innovation management domain and shows that GenAI has a positive impact on important elements of the Knowledge Spillover Theory of Entrepreneurship, emphasizing its potential impact on innovation, entrepreneurship, and economic growth. Future research should further explore the dynamic interaction between GenAI and creative processes.