Cloud Wars Live with Bob Evans

Key Takeaways

Session overview: AI is a transformative technology where security is lagging dangerously behind. Polino's session, "A Guide to Security Roles in AI Transformation (Implementation)," will explore why it's critical for organizations to reassess current roles, controls, and systems and proactively design security strategies specifically for an AI-driven environment.

Guardrails: AI systems can be easily manipulated through indirect prompts or parameter framing, making it essential to enforce extremely strict guidelines and access controls to prevent unintended exposure of sensitive data.

Exploring security with leaders: Organizations must proactively define security policies and controls for AI now to prevent users from going rogue or turning to shadow IT, because inaction will only amplify risk as sensitive data inevitably leaks into unsecured public AI tools.

Event takeaways: Polino notes the importance of events like this because they bridge the knowledge gap between AI leaders and everyday business users by equipping them to understand AI early and effectively transfer that knowledge across their organizations. "AI is coming, whether you want it or not. The goal here is to figure out how to use it appropriately, how to make it as safe as you possibly can, and mitigate those risks inside your organization."

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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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In today's Cloud Wars Minute, I explain why Oracle’s massive RPO growth proves demand for AI infrastructure is real, not a bubble.

Highlights

00:00 — For the last several weeks, we've all been hearing gloom and doom, there's going to be AI overcapacity for data centers, and then talking about all these things that Oracle can't do. I want to talk about this in the context of Oracle's terrific Q3 numbers that came out earlier this week. I hope what they'll do as a residual effect is shut the pie holes of some of these just lame-brain skeptics .

01:15 — So I hope some of those people either be quiet, get off to the sidelines, or maybe think a little bit more about how the world is changing, and the tech vendors, especially the ones in the Cloud Wars Top 10, have to change to meet these new times. So let me describe some of what's behind that in these big numbers from Oracle.

01:38 — Like I said, there is RPO, remaining performance obligation, up 325%. It added $29 billion of new RPO in the quarter. The cloud business, 44%. It's $8.9 billion, very, very strong there. Inside some of those numbers, its multicloud database up 531%. It's a huge jump. That's where Microsoft, Amazon, and Google Cloud all sell the Oracle database to their customers.

02:22 — So a big, big business there, the AI infrastructure business overall up 243%, and the RPO is now up $553 billion, well over half a trillion dollars of contracted business that Oracle has not yet recognized as revenue. So it shows enormous growth for the future. Yet in spite of all these things, we've heard relentlessly from these Chicken Little types.

03:04 — First, that there's an AI data center buildout. This is all a bubble. It's going to explode. There's all these hundreds of millions of dollars in CapEx chasing a dream that will never happen. We've heard a lot about that Oracle, which earlier this year said it's going to use debt financing to fund its data center expansion. That that's terrible.

04:18 — Oracle's wildly profitable. It's in great shape on this. There are still other cry babies who are running around saying that the new CEOs aren't ready to handle this. They were supremely in charge on this earnings call, very, very clear, concise descriptions of the strategy and what's going forward.

05:02 — Now, looking ahead this fiscal year, which ends May 31, Oracle's projecting total revenue $67 billion. A year out from that, fiscal 27, it's projecting total revenue for the company of $90 billion. So the whole company growing 34%, turbocharged by what it's doing in the cloud and AI. This is an extraordinary time to be alive. Don't listen to the doom and doomsday folks.

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In this episode of the AI Agent & Copilot Podcast, Giuseppe Ianni, host of the show, is joined by Diego Araujo, Founder and Chief AI Architect at Fusion Flow Software. Their conversation explores how enterprises are adopting AI agents and copilots within ERP environments, particularly Microsoft Dynamics 365 Finance & Operations.

Key Takeaways

Start with a “Winning” Use Case: Successful AI adoption begins with identifying a high-impact, low-effort opportunity that delivers immediate value. Araujo stresses the importance of choosing use cases that are repeatable and measurable. He explains that organizations must deliberately identify early wins to build momentum and credibility across teams.

User Adoption Determines Success: Technology alone does not guarantee successful AI implementation — user adoption does. Araujo emphasizes that fear and skepticism often prevent employees from embracing AI tools. He recommends involving subject matter experts and users early in the process so they feel ownership over the solution.

Governance and Safety Must Be Built In: Enterprise AI systems require robust governance frameworks to ensure compliance, security, and control. Araujo highlights the importance of planning governance early in the process, particularly when deploying agents inside ERP environments that manage critical business processes. He cautions organizations to build mechanisms that prevent agents from causing unintended outcomes. “You don’t want an agent going rogue,” he explains.

Measure Value with Clear Metrics: AI initiatives must demonstrate measurable impact rather than relying on hype or novelty. Araujo stresses that organizations should identify metrics that directly tie AI capabilities to business outcomes. “Coolness is not a factor,” he explains. Instead, companies must define operational indicators such as efficiency gains or cycle time reductions.

AI Agents Enable a New Workforce Model: Araujo describes a major shift in how employees interact with technology as AI agents become widely adopted. He suggests that individuals will increasingly act as managers of multiple digital agents that execute tasks autonomously. This mindset shift opens new productivity opportunities for organizations.

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In today’s Cloud Wars Minute, I look at ServiceNow’s new Autonomous Workforce and what it means for the future of the digital workforce.

Highlights

00:03 — As companies become more familiar with the scope and capabilities of agentic AI, they're seeking more efficient ways to integrate these features into their workflows. And in line with this trend, ServiceNow has launched the Autonomous Workforce: teams of AI specialists that will enhance teams with domain-specific AI knowledge.

00:29 — So how does the Autonomous Workforce operate in practice? Well, the AI specialists deployed by the system have defined roles and work alongside human team members. ServiceNow explains that this shift represents a move away from AI agents that complete individual tasks to teams of AI specialists that take on specific roles.

00:57 — These specialists execute entire workflows from start to finish autonomously. Teams can onboard pre-skilled AI specialists with just a few clicks. These specialists are familiar with their roles, permissions, and, crucially, the historical enterprise context. Companies can scale the scope of the specialists on demand to match spikes in activity.

01:20 — The first out-of-the-box specialist is theLevel 1 Service Desk AI Specialist which can autonomously diagnose and resolve typical IT support requests like password resets or network troubleshooting. Proof of concept for this new system lies with ServiceNow, where the Autonomous Workforce is already handling over 90% of employee IT requests.

02:01 — What's truly remarkable is the redefinition of the work of the digital workforce. Having a context-aware, independent worker for specific tasks is a really outstanding achievement and development. It embodies the futuristic vision of a robotic worker and, in reality, is somewhat more streamlined than many of the widely dispersed agentic systems that I've come across today.

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