In this episode, Maribel speaks with Shub Bhowmick, the CEO and Co-founder of Tredence on how its using AI internally and externally. Bhowmick also provides advice on what's important for enterprise buyers looking to leverage AI.

Takeaways

• The shift from proof of concept to proof of value is crucial for businesses.
• AI is enabling organizations to achieve more with fewer resources.
• Agentic solutions are becoming increasingly relevant in various industries.
• Internal innovations at Treatance are focused on developing interconnected AI agents.
• Organizations must prepare for a future where they need to do more with less.
• Crawl, walk, and run is a practical approach to AI implementation.
• Creating a robust monitoring and operations foundation is essential.
• Small language models can be more effective and cost-efficient than larger models.
• AI can significantly enhance productivity and creativity in the workplace.
• Health and personal well-being are important considerations in a fast-paced professional environment.

Sound Bites

• "Proof of value is the new proof of concept."
• "AI is enabling you to do more with less."
• "Agents are like smart interns, very analytical."
• "The speed of AI is moving much faster."
• "AI can 10x your productivity."
• "Crawl, walk, and run with AI implementation."
• "Small language models are the new thing."

Chapters

00:00
Introduction to Treatance and AI Trends

07:28
Emerging Use Cases in AI

11:46
Real-World Applications of AI in Business

18:33
Internal Innovations at Treatance

30:33
Advice for Organizations on AI Implementation

Summary

In this conversation, Maribel Lopez speaks with Markus Nispel about the integration of AI in networking solutions, particularly at Extreme Networks. They discuss the evolution of AI capabilities, the importance of data governance, and the role of AI in enhancing operational efficiency and security. Markus emphasizes the need for trust in AI systems and the potential of agentic AI to transform networking operations. The discussion also touches on the challenges of skill development and the future of AI in the industry.

Extreme Networks, trusted by tens of thousands of customers globally, delivers AI-native cloud networking solutions that seamlessly connect people, applications, data, and devices.

Info on Extreme Networks Platform One: https://www.extremenetworks.com/platform-one and an explainer video https://vimeo.com/1036922077/58472f1411?ts=0&share=copy.

Takeaways

• AI has been integrated into networking solutions for measurable business value.
• Data quality is crucial for effective AI implementation.
• Generative AI can significantly reduce the time for knowledge acquisition.
• Agentic AI combines various capabilities for enhanced networking solutions.
• Trust and transparency are essential for AI adoption in enterprises.
• AI can optimize security policy configurations and reduce attack surfaces.
• The orchestration of agents is vital for achieving automation in networking.
• AI's role in skill development is critical for new employees.
• The future of AI in networking will involve more autonomous systems.
• Continuous feedback loops enhance trust in AI systems.

Sound Bites

• "AI allows for a consistent support experience."
• "Data governance is critical for AI systems."
• "The orchestration of agents is key to automation."
• "Trust is essential for AI adoption in enterprises."
• "The future is dynamic with AI advancements."

Chapters

00:00 Introduction to AI in Networking

03:40 Evolution of AI Integration in Networking Solutions

06:54 Understanding AI's Unique Positioning in Networking

10:18 AI's Role in Skill Development and Knowledge Acquisition

13:02 Defining Agentic AI and Its Current Capabilities

16:54 The Importance of Orchestration in AI Systems

19:45 Addressing Trust and Resistance in AI Adoption

23:19 Demonstrating ROI from AI Implementations

25:29 Future of AI: The Rise of Agentic Systems

Show Notes:

In this episode of "AI with Maribel Lopez," host Maribel Lopez sits down with Vijay Sundaram, Chief Strategy Officer at Zoho, at Zoho Day 25 in Austin, Texas. They discuss Zoho's strategic evolution and approach to AI.

Key Highlights:

• Zoho's Market Evolution: Vijay explains how Zoho has expanded from primarily serving small and medium businesses to increasingly being adopted by larger enterprise customers worldwide. This evolution has happened naturally as their products became more sophisticated and larger customers discovered them.
• Enterprise Adaptation Challenges: To serve enterprise customers, Zoho had to make changes in three areas:
  1. Technology (their strength as a product-driven company)
  2. Operations (building expertise in account management, solutions consulting, etc.)
  3. Transitioning from an inbound to outbound business model
• AI Implementation Strategy: Vijay clarifies that while generative AI has recently captured public attention, Zoho has been implementing various AI technologies (machine learning, NLP, video recognition) for over a decade. Much of this AI has been "headless" - working behind the scenes in applications rather than through conversational interfaces.
• Three Levels of AI: Zoho approaches AI implementation through:
  1. Contextual AI within business applications
  2. Interactive AI for specific purposes
  3. Expert-level insights that enable non-experts to gain valuable business intelligence
• Platform Approach: By integrating applications and creating a comprehensive platform, Zoho can leverage data across domains (finance, sales, HR, operations) to provide more valuable AI-driven insights.
• AI Market Shift: Vijay predicts that AI differentiation will increasingly move from foundational models to the application layer, where companies like Zoho can add value through their access to business data across domains.
• Privacy and Security: Zoho maintains a strong stance on privacy (no trackers on their websites) and has built a "trust layer" into their platform to ensure proper data access controls for AI interactions.