Cognizant breaks through enterprise agentic orchestration barrier

Enterprise leaders face a critical challenge in 2025. While the promise of agentic AI represents the enterprise’s next frontier in artificial intelligence, most currently available solutions fail to deliver genuine multi-agent capabilities at enterprise scale. Organizations are struggling to evolve beyond isolated AI implementations, and they are trapped between the aspiration of truly autonomous, collaborative AI systems and the reality of siloed, limited-function tools.

Cognizant’s introduction of the Neuro® AI Multi-Agent Accelerator directly addresses this leadership challenge. Rather than adding to the noise with another standalone AI solution, Cognizant has focused on solving the core problem: how to enable genuine collaboration between multiple AI agents across enterprise functions.

The current agentic AI landscape reveals a fragmented market struggling to meet enterprise needs

While 2024 saw an explosion of solutions labeled as “autonomous agents,” closer examination reveals many of these offerings lack fundamental agentic capabilities. True agency requires more than just automated decision-making—it demands the ability to understand context, adapt to changing conditions, and, most crucially, collaborate effectively with other agents to achieve broader organizational goals.

The current agentic market can be categorized into three approaches:

1. Rebranded tools: The most common category consists of conventional automation solutions superficially relabeled with agentic terminology. While these tools may handle specific tasks effectively, they lack true autonomous capabilities and ultimately perpetuate the problem of AI silos within organizations.
2. Narrow domain specialists: The second category features genuinely autonomous agents that operate effectively within specific domains. While more advanced than simple rebranding, these solutions still lack the ability to collaborate meaningfully with other systems, contributing to the ongoing fragmentation of enterprise AI capabilities.
3. True multi-agent systems: The most sophisticated category comprises systems capable of both autonomous operation and inter-agent collaboration. Until recently, solutions in this category existed primarily as proofs-of-concept, lacking the scalability and enterprise-grade features required for broad adoption.

This fragmentation reflects broader challenges in enterprise AI adoption. For instance, our research shows that only 8% of organizations have achieved enterprise-wide integration of GenAI, with the remaining 92% still in the early stages, running exploratory pilots or limiting deployment to specific tasks or departments (see Exhibit 1). Most AI implementations operate as standalone solutions, unable to share context or collaborate across functional boundaries. This siloed approach not only limits the potential value of AI investments but fundamentally constrains an organization’s ability to achieve broader business objectives.

Exhibit 1: Only 8% of organizations have achieved organization-wide GenAI integration

Source: HFS Research, 2025

This fragmented landscape presents significant challenges for enterprise leaders attempting to implement effective agentic AI strategies. Organizations find themselves managing multiple disconnected AI capabilities, each operating in isolation and unable to contribute to broader organizational objectives.

These market challenges demand a fundamentally different approach to enterprise AI orchestration, one that prioritizes coordination over individual capability. This is where Cognizant’s strategic response stands apart.

Cognizant’s Neuro AI Multi-Agent Accelerator represents a fundamentally different approach to enterprise agentic systems

Rather than enhancing individual agent capabilities, Cognizant has prioritized solving the orchestration challenge plaguing enterprise AI implementations. Their accelerator addresses three critical barriers to effective multi-agent deployment: the complexity of agent coordination, rapid scaling challenge, and vendor lock-in risk.

Core features of the multi-agent accelerator:

• Pre-built multi-agent networks: Neuro AI provides pre-configured templates for various enterprise functions, such as sales, marketing, and investor relations, as well as industry-specific areas, such as supply chain management. These templates accelerate deployment and reduce complexity.
• Natural language customization: Businesses can quickly create and adapt multi-agent networks using natural language descriptions, enabling faster tailoring to specific scenarios and unique client needs.
• Orchestration framework: A built-in coordination layer facilitates seamless communication and task routing between agents, automatically managing dependencies and resolving conflicts.
• Adaptive scaling architecture: Dynamic resource allocation and load balancing enable agent networks to scale up or down based on organizational requirements, ensuring flexibility and operational efficiency.
• Multi-vendor integration: The platform offers a flexible infrastructure that supports various large language models (LLM) and cloud providers, enabling organizations to optimize costs and performance without the need for system rebuilds.

The Neuro AI Multi-Agent Services Suite transforms how organizations deploy and manage AI agents at scale. By providing both the technical foundation and methodological framework for enterprise-wide agent networks, Cognizant gives organizations the tools to move beyond isolated implementations toward truly collaborative systems with a business context.

Early implementations demonstrate how this orchestrated approach can tackle complex challenges isolated AI systems cannot address. For instance, an insurance company improved investor relations and call analysis, while a healthcare organization achieved faster medical appeal processing through a contract negotiator agent network.

The Neuro AI platform represents a fundamental shift in enterprise AI architecture—moving away from disconnected point solutions toward intelligent, self-coordinating networks of AI capabilities.

The Bottom Line: The next evolution of enterprise AI isn’t about building better individual agents; it’s about orchestrating networks of specialized AI agents working seamlessly across your organization.

Cognizant’s new accelerator and services suite offers a promising path forward by addressing the orchestration challenge head-on. However, their success will depend not only on delivering results across diverse enterprise environments but also on organizations’ readiness to adapt, reskill, and align their operations to embrace this transformation fully.