In today’s enterprise landscape, AI agents are a hot topic, with many companies experimenting with their implementation. However, there is a growing concern that the hype surrounding AI agents may not be backed up by real-world use cases. Despite this skepticism, companies like Block and GlaxoSmithKline are exploring proof of concepts in areas such as financial services and drug discovery, showing early signs of ROI.
Block, a company with a focus on innovation, has introduced an interoperable AI agent framework called “Goose.” This platform has automated tasks for software engineers, saving them valuable time by generating code, debugging, and filtering information. Goose acts as a digital teammate, integrating with company tools and expanding its capabilities as needed, all while maintaining a user-friendly interface that feels like working with a single colleague.
GSK, a leading pharmaceutical developer, is leveraging multi-agent architectures to accelerate drug discovery. By combining domain-specific language models with ontologies and rigorous testing frameworks, GSK’s scientists are able to analyze large datasets, plan experiments, and surface hypotheses. The company emphasizes the importance of ongoing testing and validation to ensure the reliability and accuracy of their AI systems, highlighting the critical role of human domain expertise in the process.