Techaisle Blog

At its recent Partner Summit, Cisco’s executive team, led by CPO Jeetu Patel, made a declaration that was as bold as it was inevitable: "Cisco is the critical infrastructure company for the AI era." For an organization built on connecting the internet, this is a profound pivot. However, according to my analysis, even this claim is too modest. Cisco is not just building infrastructure; it is building the integrated stack to simplify and secure customer deployments. A more accurate title is the "Distributed AI Infrastructure Orchestrator." This pivot to orchestration is not one Cisco can make alone. It is a co-dependent strategy built to capture a once-in-a-generation install base refresh—an opportunity CEO Chuck Robbins pegged at $40 billion for Cisco. From my Techaisle analysis, Cisco's blueprint for capturing this opportunity rests on three interdependent pillars:

1. A Reframed Platform Strategy: Solving the core-to-edge infrastructure and data barriers to AI.
2. A Comprehensive Security Doctrine: Weaving trust into the fabric of the network as a prerequisite for AI adoption.
3. A Modernized Economic Engine: The new Cisco 360 Partner Program is designed to shift partner business models from resale to high-value lifecycle services.

1. Reframing the Platform: Beyond "AI Infrastructure"

Jeetu Patel’s claim is the new north star, but I believe "critical infrastructure for the AI era" is too modest a description. It fails to capture the scale of Cisco’s ambition. Cisco’s strategy is designed to address what it identifies as the three fundamental "impediments" holding back AI: infrastructure constraints, a trust deficit, and a data gap.

As an analyst who has followed Zoho for many years, interacting with their partners and extensive customer base, I have tracked Zoho’s steady evolution from a collection of apps to a true platform. With its November 2025 release, Zoho is making its most profound market statement yet. This is not just a product update; it represents a fundamental strategic shift from selling a software suite to delivering a unified business operating system.

For years, the market has compelled organizations to assemble a constellation of "best-of-breed" applications, resulting in a fragmented, costly mess that Zoho aptly calls the integration Frankenstein problem. This release is Zoho's definitive answer, designed to replace that complexity with a new core value proposition: operational peace of mind.

The Strategic Bridge: A Logical Chain to Value

The three pillars of this release—Experience, Integrations, and Intelligence—are not separate features; they are interdependent. They are a single, logical chain of cause and effect that forms Zoho's entire value proposition. This strategic unification arrives at a critical moment, as businesses seek to harness the power of AI and move beyond the fragmented, app-centric model of the past. This chain is built as follows:

1. The Unified Experience is the Promise. It serves as the core promise to the user: a simple, coherent OS where all business functions are in one place
2. The Deep Integration is the Technical Enabler. It makes the promise possible, providing the essential, native plumbing that allows 50+ applications to act as one.
3. The Unified Intelligence is the Ultimate Payoff. Because the experience and data are unified, Zoho can deliver on the true goal of AI: intelligence that is powerful because it is both holistic and contextual.

The Pillars of Unification

The technology market is awash in "Generative AI." We are saturated with demonstrations, pilots, and proofs of concept (POCs). Yet, for most organizations, the path from a compelling demo to scaled, enterprise-wide production remains elusive. The gap is fraught with challenges, not least of which are security, governance, and a clear return on investment.

In a recent analyst briefing, Google Cloud, led by Hayete Gallot, President of Customer Experience, articulated a strategy that signals a distinct and significant pivot. The narrative is moving decisively from "Generative AI" as a standalone technology to "Agentic AI" as a governed, integrated business system.

This is not a mere semantic shift. It is a fundamental reframing of the problem and the solution, moving the conversation from "what a model can do" to "what a system of agents can achieve for the business." This agent-centric strategy is built on three core pillars: a platform for governance, a framework for creating new agentic architectures, and a GTM model for partner-led scale.

The "Why": Solving for "Rampant Agents"

The generative AI market is currently a chaotic mix of boundless promise and paralyzing complexity. For enterprise customers, the landscape is a minefield. Do they risk cost escalation and vendor lock-in with proprietary, API-first models, or do they brave the "wild west" of open-source models, complex hardware requirements, and fragmented tooling? This dichotomy has created a massive vacuum in the market: the need for a trusted, stable, and open platform to bridge the gap.

Into this vacuum steps Red Hat, and its strategy, crystallized in the Red Hat AI 3.0 launch, is both audacious and familiar. Red Hat is not trying to build the next great large language model. Instead, it is making a strategic, high-stakes play to become the definitive "Linux of Enterprise AI"—the standardized, hardware-agnostic foundation that connects all the disparate pieces.

The company's legacy motto, "any application on any infrastructure in any environment", has been deliberately and intelligently recast for the new era: "any model, any hardware, any cloud". This isn't just clever marketing; it is the entire strategic blueprint, designed to address the three primary enterprise adoption-blockers: cost, complexity, and control.

The Engine: Standardizing Inference with vLLM and LLMD