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.

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

For years, midmarket businesses have been caught in a difficult position, forced to choose between the chaos of disparate, best-of-breed point solutions and the restrictive "walled gardens" of single-vendor platforms. At WebexOne 2025, Cisco presented a compelling third way: a vision of "Connected Intelligence" that delivers the power of a deeply integrated, cross-portfolio platform without the penalty of a closed ecosystem. This strategy, which Techaisle defines as Pragmatic Platformization, is a masterclass in meeting customers where they are. It is also the realization of a vision Techaisle first articulated in our 2018 white paper, "Interwork: the next step in connected businesses." In that analysis, we identified that the future of business IT would be defined by an 'Interwork platform' built from the interconnection of seven key domains, including "Connected security," "Connected collaboration," and "Connected insights." Cisco's 'Connected Intelligence' strategy is a powerful, real-world execution of this very concept. By combining the unique strengths of its networking, security, and collaboration portfolios while simultaneously forging deep, native integrations with its staunchest competitors, Cisco is building a platform that is uniquely suited to the heterogeneous and investment-conscious nature of the midmarket.

The 'One Cisco' Advantage: From Metal to Model

The foundation of the Connected Intelligence vision is the "true platform effect" that comes from leveraging Cisco's entire technology stack. This is not just a marketing concept; it is an organizational and engineering reality that allows Cisco to solve problems that no pure-play collaboration or networking vendor can address alone.

The most powerful new expression of this is the extension of AI Canvas to the collaboration portfolio. Initially announced for networking and security, AI Canvas is a collaborative, AI-powered troubleshooting tool. Integrating collaboration data means an IT admin can now investigate a "poor call quality" complaint and see correlated data from the Webex application, the user's Meraki access point, and the underlying Catalyst switch, all in a single, "multiplayer" interface. AI Canvas can then identify the root cause—such as a misconfigured QoS policy—and suggest a fix that can be applied in minutes, not days.

The narrative surrounding Artificial Intelligence in the workplace is undergoing a seismic shift. For the past several years, the conversation has been dominated by assistive AI—tools that could listen, transcribe, and summarize, acting as diligent but passive scribes. At its WebexOne 2025 event, Cisco signaled the definitive end of that era and the dawn of a new one: the age of Agentic AI. This is not merely an evolution; it is a re-imagining of AI's role from a helpful assistant to a proactive, autonomous "agentic teammate". While the scale of this vision is enterprise-grade, Techaisle analysis indicates that its most profound impact may be felt within the midmarket, where the automation of complex workflows is not a luxury, but a critical engine for growth and competitive advantage.

From Passive Assistance to Proactive Action

Cisco’s core message was a move "from this kind of notion of chat bots that intelligently answered our questions to agents that are going to conduct tasks and jobs almost fully autonomously on our behalf". This transition is the central pillar of its “Connected Intelligence” vision and is embodied by the introduction of five new AI Agents for the Webex Suite. These agents are designed to move beyond reporting on what happened in a meeting to actively participating in the work that follows.

• The Notetaker Agent: This agent captures summaries and action items from in-person conversations using the Webex app or a Cisco device.
• The Polling Agent: It contextually listens to meeting conversations and proactively suggests live polls to gauge team sentiment or gather immediate feedback, eliminating the friction of creating them manually.
• The Task Agent: Going beyond listing action items, this agent can be delegated to complete them—for example, by automatically creating a Jira ticket based on a technical discussion.
• The Meeting Scheduler Agent: This agent intelligently identifies the need for a follow-up, finds a suitable time for all required participants, and even drafts an agenda based on the prior conversation’s context.
• The Receptionist Agent: Leveraging technology from its Contact Center portfolio, this voice-enabled agent can handle routine inbound calls, answer queries, and route customers, acting as an AI-powered automated attendant for Webex Calling.

The Midmarket Perspective: A Productivity Force Multiplier