Cloud Wars Live with Bob Evans

Key Takeaways

Shift in AI focus: As Director of AI at Armanino, Montgomery explains that organizations are shifting from last year’s AI experimentation and demos toward defining real business use cases and operationalizing AI; embedding it into processes, insights, governance, and workforce interactions to transform how the business runs.

Session overview: One of her sessions, "From Insight to Intuition: Designing Copilot Experiences that Understand People," will provide “a practical blueprint for designing Copilot and agent experiences that people can trust and use,” addressing the gap between building AI systems and thoughtfully designing how employees interact with them.

Learning objectives: Turning on Copilot often leads to early experimentation but a dip in trust as users encounter vague outputs, prompt fatigue, and unclear accountability because the experience wasn’t intentionally designed. Montgomery's masterclass introduces an “agent experience” framework called CARE — context, awareness, relationships, and empathy — to help organizations design AI systems that are trustworthy, accountable, and effective in business workflows.

Event relevance: The event, explains Montgomery, comes at “an inflection point with AI adoption across businesses,” bringing together technical and business leaders to help organizations move from exploring AI’s possibilities to deploying it responsibly and at scale across their operations.

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Key Takeaways

Smart friction: AI prioritizes speed and efficiency, but in retail experiences where shoppers value engagement, intentional friction can enhance customer satisfaction and ultimately drive better returns, giving rise to the idea of "smart friction."

Use case: Trader Joe’s, for example, deliberately avoids self-checkout to create smart friction, using wait time to immerse customers in design, promote product discovery, and foster interactions with staff that enhance the overall brand experience. By preserving the elements that make its brand special rather than blindly automating for speed, the grocery retailer has been able to stay competitive despite having fewer locations than many rivals.

Don't over-automate: While many AI solutions will benefit enterprises, organizations should be careful not to automate away the core elements that define and differentiate their brand.

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In this episode of the AI Agent & Copilot Podcast, Giuseppe Ianni, host of the show, is joined by Andrea Pinillos, Senior Technical Program Manager at Microsoft, to discuss practical strategies for enterprise adoption of AI agents and copilots. Pinillos shares insights from her work leading internal Microsoft tooling and previews her upcoming session at the 2026 AI Agent & Copilot Summit NA.

Key Takeaways

Democratizing AI with Simple Tools: Pinillos emphasizes that organizations don’t need complex infrastructure to begin using AI agents. By combining tools like Excel and Copilot Studio, teams can quickly prototype useful solutions such as employee directories. Her goal is to lower barriers to adoption so more teams can experiment safely.

Governance Must Come First: One of Pinillos’ strongest recommendations is to establish governance before deploying AI agents at scale. Organizations often rush into building tools without clear rules about ownership, permissions, or oversight. According to Pinillos, responsible adoption starts with planning. She stresses the importance of “making sure that your organization is making [this] an important factor."

Real-World Demonstrations Accelerate Adoption: Pinillos’ summit session focuses heavily on practical learning through demonstration. Rather than discussing theory, she will show attendees exactly how to connect Copilot Studio to an Excel data source, build actions, and enable conversational interaction with data. She believes hands-on demonstrations help organizations move from curiosity to implementation.

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In today's Cloud Wars Minute, I explore how Microsoft is using Copilot Studio and multi-agent orchestration to dramatically improve customer support performance.

Highlights

00:09 — Now, one of the best ways to assess the impact of Microsoft Copilot is to examine case studies of the technology in action. Microsoft has announced details of a recent project delivered through Copilot Studio, aimed at enhancing the customer support experience on microsoft.com, building on the Ask Microsoft web agent created using Microsoft Copilot Studio.

00:51 — This new approach resulted in a 61% reduction in latency and up to 70% fewer human escalations. The Microsoft team tested and refined the original web assistant, getting it live within just a few weeks using Copilot Studio tools.

01:11 — However, it was the facilities multi-agent orchestration feature that truly enhanced this project, enabling the team to connect the main agent to sub-agents with domain-specific knowledge in areas such as Azure or Microsoft 365 .

01:34 — Firstly, Microsoft is presenting a very tangible use case for Copilot Studio here. Secondly, it highlights the speed at which Copilot Studio can be used to rapidly deploy and easily edit agentic workflows. And finally, it serves as a really good advertisement for multi-agent architecture and orchestration, which I believe unlocks the most capable AI performance.

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In this episode of Cloud Wars Live, Bob Evans speaks with Bonnie Tinder, founder and CEO of Raven Intelligence, about the surge of hype, confusion, and opportunity surrounding AI in enterprise technology. As headlines claim AI could replace traditional software and “vibe coding” threatens SaaS vendors, Tinder brings a grounded perspective from years of advising organizations on enterprise systems like Salesforce, Workday, and SAP. Their conversation explores what AI can realistically do today, why enterprise software remains critical, and how companies can move forward without falling for hype.

Episode 58: AI Hype vs. Reality

The Big Themes:

Why “Vibe Coding” Won’t Replace ERP: The idea that AI-powered “vibe coding” could replace enterprise applications is a popular narrative, but both Evans and Tinder challenge its practicality. Even companies developing cutting-edge AI models are still relying on traditional enterprise systems. For example, Tinder notes that AI companies themselves are hiring administrators for established software platforms rather than replacing them.

Leadership Must Guide AI Adoption: The discussion also emphasizes that AI adoption cannot be left solely to technology teams. According to Evans, the entire executive leadership team, especially the CEO, needs to be actively involved in defining how AI will shape the organization. AI initiatives affect workflows, job roles, data governance, and competitive strategy. Without clear leadership alignment, different departments may pursue conflicting approaches, slowing progress or introducing risk.

Fear and FUD Are Slowing Progress: Ironically, the greatest threat from AI hype may be paralysis. Tinder argues that fear, uncertainty, and doubt in the market are causing many companies to delay decisions altogether. Organizations worry about choosing the wrong tools, implementing technology too early, or missing the next wave of innovation. This hesitation can prevent companies from making meaningful progress. Instead of waiting for perfect clarity, organizations should take practical steps.

The Big Quote: “You can vibe code your way around [a] notion or a content system, that's way different though, than having an in-house solution for an enterprise software."

More from Bonnie Tinder:

Connect with Bonnie on LinkedIn.

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