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That said, getting out of the pilot phase and into everyday business applications is proving to be the biggest hurdle for any AI project. HBR has estimated that AI projects have a failure rate as high as 80 %. In fact, according to an IBM study of over 8,500 IT professionals worldwide, limited AI skills and expertise, data complexity, and ethical concerns were cited as top barriers to AI deployments.
In addition, other studies show many projects fail to scale due to legacy architecture dependencies, but also due to costs and performance in scaling something so complex and unstructured. Even when projects do get up and running, data quality, governance, security and tech workflow integration hurdles remain.
Meet the AI force multiplier: event-driven architecture and the event mesh
At the heart of these challenges lies a critical deficiency – the absence of real-time, contextual information flow. Traditional batch processing and static data models still in use by many organizations fall short of providing dynamic business environments where decisions, often that have to be made in splitseconds if you consider financial trading, are the make or break of trading opportunities.
An event mesh, underpinned by event-driven architecture( EDA), is the missing ingredient that promises to transform enterprise AI into a realtime, context-aware powerhouse. An event mesh is an interconnected network of event brokers that dynamically routes event-driven information between all kinds of applications and devices across environments and around the world.
Here’ s where the event mesh shines for AI deployment. It provides the decoupling needed for rapid development and change and it delivers on the event-driven architecture that allows for managing rate mismatch, supporting different applications with messaging patterns, and delivering efficiency needed to scale horizontally and vertically.
When you apply the architectural pattern enabled by the event mesh across agentic AI use cases, you essentially create a flexible, real-time data distribution network that enables various AI models to access and react to relevant data streams instantly.
And now meet the agent mesh
While an event mesh enables real-time data flow and dynamic routing across the enterprise, an agent mesh takes this further by introducing intelligent agents that can autonomously reason about, and act on, this information flow.
An agent mesh is a framework that allows you to build a network of AI agents overseen and controlled by a dynamic orchestration layer, allowing complex tasks to use multiple agents and bring their results together in a data management system. Agent mesh gateways allow access to this system for many different use cases, each with its own type of input interface and authorizations.
Essentially, organizations can enable truly autonomous Agentic AI systems that can manage
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