At Frontier AI, we recognize that the journey to deploying generative AI in existing businesses is both exciting and fraught with complexities. In our latest guide, presented by our Director, Paul Golding, we elucidate the stark difference between merely enhancing existing strategies with AI and the truly innovative approach of developing new strategies because of AI. We explore the challenges faced when adding large language models to businesses and emphasize that fully working AI is highly task-dependent, requiring more than just a large language model. From building a model from scratch to fine-tuning and prompt engineering, we discuss the vast set of opportunities and the need for a holistic approach in AI innovation.

With real-world examples ranging from unsecured lending to the travel industry, we shed light on how large language models are but one component in a multi-faceted solution. Our analysis highlights the importance of explainability, data strategy, and the innovative use of underlying architectures. We end with a cautionary note for incumbents, pointing out the edge that proprietary data can provide, while underlining the necessity of a comprehensive AI innovation strategy. It's not just about bolting on a large language model; it's about a methodical and innovative approach to extracting meaningful lasting value from AI. For more insights into our comprehensive method of combining design, innovation, and AI, we invite you to get in touch with us.