Cloud Wars Live with Bob Evans

Key Takeaways

Overview: Companies are drowning in AI tools, most of which "do not talk to each other." Today, Microsoft announced Microsoft 365 E7: The Frontier Suite, officially launching May 1st for $99. The suite brings together Microsoft 365 E5, M365 Copilot Wave 3, and Agent 365.

Manage agents: IDC projects 1.3 billion AI agents by 2028, creating major governance, access control, and data management challenges that Agent 365 addresses by giving teams a single place to track, secure, and manage them all.

Big idea: Work IQ, which will be explored at AI Agent & Copilot Summit, signals that Copilot has gone mainstream, with 160% YoY growth and large-scale enterprise deployments. "This isn't experimentation anymore. This is enterprise AI going mainstream."

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In today's Cloud Wars Minute, I analyze Oracle’s projected Q3 numbers and the explosive growth of its cloud and AI infrastructure business.

Highlights

00:02 — Tomorrow, March 10, Oracle releases its Q3 numbers. I think these will be some of the most interesting we see from any of the Cloud Wars Top 10 companies, because relative to Oracle's size, its growth rates are up near the very top, and its RPO growth has been absolutely astronomical.

00:58 — So you might think of it as pipeline or backlog. This is money that's again fully contracted. It is not yet recognized as revenue, but it's an indication of where customers in the future are putting their hearts, minds, and wallets. I'll take a look at some key numbers for Oracle and compare the Q2 results with my Q3 projections.

02:02 — So for Q2, Oracle's RPO grew in Q2 over Q1 $68 billion. It had some huge deals in there with Meta and NVIDIA. It'll still do very well adding another $59 billion to its RPO. Now we look at its cloud revenue. For Q2 it was a total of $8 billion, up 34%.

03:13 — The OpenAI deal is massive, probably around $300 billion, but there's a lot more in there beyond that $300 billion. Oracle is emphasizing that it has a wide-ranging cloud infrastructure and AI infrastructure business that includes traditional moves from on-premise to cloud and other services beyond the OpenAI deal.

04:06 — Google Cloud hit almost $18 billion in its quarter. Now Oracle is almost half the size of Google Cloud, but it's got this tremendous backlog of future business because of capabilities around AI training, AI inferencing, and its core businesses as well.

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In this AI Agent & Copilot Minute, Mason Siefert explores how grocery retailers are accelerating AI adoption behind the scenes — empowering store associates and operational teams — even as consumer trust in customer-facing AI tools remains limited.

Key Takeaways

Consumer Trust Gap: Despite the rapid rollout of advanced retail AI tools, adoption among consumers remains limited. A recent consumer trend study shows only about 15% of shoppers actively use customer-facing AI solutions, even with innovations like Kroger’s personal shopping assistant. Concerns about hidden algorithm pricing and lack of transparency have contributed to skepticism, leaving retailers operating in what some experts describe as a “gray zone” of AI adoption.

Associate-Focused AI: Rather than waiting for shoppers to embrace AI fully, grocery executives are prioritizing AI tools designed for store associates. Platforms like Google’s virtual assistant Sage provide employees with a centralized system to manage scheduling, payments, and daily operational tasks. By focusing on workforce enablement, retailers can immediately drive efficiency and productivity while indirectly improving the overall customer experience.

Operational Optimization: Enterprise AI systems are increasingly being deployed to streamline frontline operations such as shift optimization, compliance monitoring, and task coordination. These tools reduce friction caused by fragmented workflows — like employees logging into multiple apps for a single task — and minimize human error. As AI handles routine operational complexity, employees can focus more on serving customers and maintaining store performance.

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In today’s Cloud Wars Minute, I explore OpenAI’s decision to adjust its trillion-dollar AI infrastructure ambitions to reassure investors.

Highlights

00:04 — Planned spending commitments amongst the Cloud Wars Top 10 companies have reached astronomical levels. This surge is in response to the anticipated demand for AI infrastructure, products, and services — a market that UN Trade and Development predicts will exceed $4.3 trillion by 2033.

00:25 — But in a trend-bucking move, OpenAI has informed investors that it's lowered its projected compute spending to $600 billion by 2030, down from the previously touted $1.4 trillion in infrastructure commitments announced in November by OpenAI CEO Sam Altman.

00:46 — And this information came from a source that spoke to the news agency Reuters. The apparent shift aims to provide a more defined timeline for planned spending, alleviating concerns for investors who might view the $1.4 trillion figure as somewhat overly ambitious.

01:06 — CNBC also reported that OpenAI's total revenue for 2030 is expected to exceed $80 billion. The revised spending plan is designed, according to sources, to align more closely with this anticipated figure and reassure investors about the company’s growth trajectory.

01:54 — The balancing act for companies like OpenAI is a delicate one. It needs to demonstrate that it has the faith and support to fully commit to AI spending while also showing restraint to its investors.

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Key Takeaways

Microsoft leads in risk detection with tools like Defender XDR, but as enterprise data environments grow in scale and complexity, organizations now need AI‑driven security that can automatically investigate and manage risk across the entire data estate, not just detect it.

With the January 2026 general release of Purview Data Security Investigations, Microsoft addresses the challenge of overwhelming data volumes by using generative AI to automatically analyze security signals across its tools and clearly summarize underlying risks so security teams can act faster and more confidently.

Purview enables these outcomes through built-in capabilities that analyze risk at scale, including deep content risk examination with scoring and remediation guidance, vector search for non‑keyword discovery, and automatic categorization by risk, sensitivity, and subject to speed incident analysis.

Purview integrates with Microsoft Sentinel’s graph to visually connect users, data, and activities across incidents and enables immediate mitigation—such as purging overshared sensitive content—allowing security teams to identify and contain risks in minutes instead of days, where speed can mean the difference between containment and a costly breach.

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