Introduction to Agentic AI in Retail
Thank you for joining us on the “Enterprise AI hub.” In this episode of the Infosys Knowledge Institute Podcast, Dylan Cosper speaks with Prasad Banala, director of software engineering at a large US-based retail organization, about operationalizing agentic AI across the software development lifecycle.
Applying AI to Validate Requirements
Prasad explains how his team applies AI to validate requirements, generate and test code, and monitor applications in production. He shares his insights on the benefits and challenges of using agentic AI in retail and provides guidance on how to get started with this technology.
Benefits of Agentic AI in Retail
Agentic AI has the potential to revolutionize the retail industry by enabling companies to automate routine tasks, improve customer experiences, and gain valuable insights from data. By operationalizing agentic AI, retailers can improve the efficiency and effectiveness of their software development lifecycle.
Challenges of Implementing Agentic AI
However, implementing agentic AI is not without its challenges. Retailers need to have the right infrastructure, skills, and culture in place to support the adoption of this technology. They also need to address concerns around data quality, security, and ethics.
Best Practices for Operationalizing Agentic AI
To overcome these challenges, Prasad shares best practices for operationalizing agentic AI in retail. These include starting small, focusing on high-impact use cases, and building a strong team with the right skills and expertise.
Future of Agentic AI in Retail
As agentic AI continues to evolve, we can expect to see even more innovative applications of this technology in retail. From personalized customer experiences to predictive maintenance, the possibilities are endless. By embracing agentic AI, retailers can stay ahead of the curve and achieve their business goals.
