Future-proof your work in the age of AI

This session will address the requirements for identifying, planning, and staging AI into any organization. With the help of Cisco infrastructure, attendees will learn the importance of integrating operational functions early into the data science, developer lifecycle, and how Cisco accelerates agility, while reducing opex costs. The content in this session will cover the AI maturity model, data science life cycle, and architecture diagrams to help companies start small with AI deployments, and scale to production ready workloads using Cisco networking, compite and software management tools including Intersight, full stack observability.

AI is the most influential technology of our time! Whether it’s chatbots, voice-enabled natural language processing IoT devices, or facial recognizing cameras, their integration into our daily lives has provided undeniable conveniences unlike anything before. But how is AI used to simplify the world of enterprise networking, security, and collaboration? To learn all about it, join us for an enlightening session where we delve into the fundamentals of how AI works, along with a deep dive into all the exciting AI technology we are building here at Cisco, which touches upon themes such as:

--The self-optimizing & healing network
--Chatbots for simplifying network and security operations
--AI for improving collaboration experience

This session will provide insight and guidance on how a Cisco Business Operations team is enabling AI within Cisco leveraging an "AI Enablement Framework" based on Cisco's AI Readiness Index. You will learn about the journey and the innovative approach integrating AI within its' business operations. This session will provide you with guidance on developing your own AI Enablement Framework, leveraging Cisco's best practices and case studies across various operational facets. You'll gain insights into the strategic alignment of people, processes, and platforms, ensuring a cohesive AI implementation strategy for your company.

Troubleshooting remains largely a manual process, with substantial time devoted to diagnosing issues. This session explores how AI/ML can expedite initial diagnoses. It delves into the suitability of various AI/ML techniques for network data and different phases of analysis, such as problem identification and diagnosis. Using real-world telemetry data as a foundation, we will collectively examine and demonstrate the use of diverse AI/ML approaches, including large language models, to pinpoint and diagnose issues. Concurrently, we will discuss the advantages and drawbacks of the various technologies employed.