In this episode of The Q&AI Podcast, Bob Friday, Chief AI Officer at Juniper Networks, sits down with Sunalini Sankhavaram, VP of Product at Juniper Networks, to dive into the transformative role AI will play in networking in the next several years. From the evolution of AI skepticism to actionable predictions for 2025, this engaging conversation unpacks the progress, challenges, and future potential of AI-Native networks.
Tune in to hear Bob and Sunalini share insights on how enterprises are transitioning from outdated, manual operations to embracing AI-driven efficiencies across industries like healthcare, retail, and higher education. Learn the difference between marketing AI and real AI, the importance of proof points in AI-Native Networking, and how deep learning and reinforcement learning are shaping next-gen networking solutions.
Key points covered:
Real AI vs marketing AI: Understanding the defining traits of genuine AI implementations and their measurable outcomes
Proof of Concept (POC): Questions enterprises should ask vendors to evaluate AI claims effectively
Predictions for 2025: Increased adoption of self-driving AI networks across wired, wireless, and SD-WAN domains, coupled with conversational interfaces revolutionizing network management
Application experience models: How AI will predict and optimize user experiences for critical applications like Zoom, Teams, and industry-critical apps
Efficacy and trust in AI: Building trust in AI-driven solutions through driver assist and self-driving modes
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We hope you enjoyed this episode!
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Chapters:
1. Introduction and welcome – Bob introduces himself and Sunalini and sets the agenda for the discussion 0:00
2. AI skepticism and adoption – The reduction of AI skepticism among enterprise customers and the current state of AI adoption in various industries 0:42
3. Real AI vs marketing AI – How to differentiate between real AI and marketing AI, and what customers should look for in AI models 1:37
4. AI in networking proof points – Key benefits covered, such as reduction in tickets and time to resolution, with examples from ServiceNow 2:28
5. Deep learning and self-driving networks – The impact of deep learning on self-driving networks and the importance of large data sets 3:53
6. Customer trust and AI efficacy – Building customer trust in AI through efficacy and the role of conversational interfaces in network management 7:25
7. Predictions for 2025 – AI in networking predictions for 2025, including self-driving networks and application experience 10:02
8. Closing remarks – Final thoughts and closing remarks from Bob and Sunalini 13:05
