AI brokers are quickly changing into the driving drive behind clever enterprise workflow automation—from processing buyer inquiries to orchestrating multi-step enterprise processes with multi-agent orchestration. However as these AI brokers tackle extra duties, their efficiency turns into tightly coupled with how briskly they will retrieve and act on information throughout enterprise methods.
That’s why Parallel Execution is a game-changer. Launched within the Kore.ai Agent Platform’s Device Builder, this functionality permits AI brokers to carry out a number of duties concurrently with instruments, as a substitute of executing every step in sequence. The consequence? Sooner, smarter, and extra environment friendly brokers that reply in actual time—and at enterprise scale.
The Drawback with Sequential Execution
Earlier than Parallel Execution, AI brokers have been restricted by a sequential job mannequin. Let’s say an agent must fetch details about a consumer—primary profile particulars from Salesforce, buy historical past out of your CRM, and help tickets from a helpdesk system. Within the conventional workflow design, the agent can be compelled to attend for the primary fetch to finish earlier than beginning the second, and so forth.
Every step would possibly take 5 seconds, leading to a 15-second delay earlier than the agent can take the following motion. This latency immediately impacts consumer expertise and undermines the promise of real-time AI-driven help.
What Is Parallel Execution in AI Brokers?
Parallel Execution solves this bottleneck by enabling AI brokers to launch unbiased duties concurrently. As quickly because the required enter—like a consumer ID—is out there, the agent can leverage instruments to set off simultaneous information fetches from a number of methods with out ready for one to finish earlier than beginning the following.
As a result of these methods (e.g., Salesforce, CRM, and helpdesk) function independently and don’t have any dependencies on one another, the agent can question them concurrently. As an alternative of 15 seconds of wait time, the agent receives all the required information in simply 5–6 seconds on common—the time it takes for the longest of the parallel requests to resolve.
This basic shift in execution dramatically boosts the efficiency of AI brokers. They not solely retrieve data quicker but additionally act on it extra rapidly, resulting in smarter selections and extra fluid conversations or processes. It’s not simply quicker—it’s operational intelligence at scale.
Parallel Execution Instance: AI Agent in Buyer Service
Image a digital customer support agent designed to help customers with personalised help. To be efficient, the agent should perceive the shopper’s present standing, latest purchases, and historic interactions—information that lives throughout a number of backend methods.
With Parallel Execution, the agent immediately dispatches three parallel information requests—one to Salesforce for contact information, one other to the CRM for transaction historical past, and a 3rd to the helpdesk database for help logs. Inside 5 seconds, the agent receives and synthesizes a full buyer profile, permitting it to reply to the consumer rapidly and precisely.
In distinction, a standard agent working with sequential execution would take 3 times longer to assemble the identical data—delaying the response, degrading the consumer expertise, and probably inflicting drop-off or frustration.
Parallel Execution unlocks a brand new degree of responsiveness, empowering AI brokers to ship quick, personalised, and context-aware interactions—whether or not in customer support, gross sales, or inside operations. These customer support brokers can be utilized together with AI for Service, a enterprise resolution to automate, personalize, and differentiate customer support interactions.
Key Advantages of Parallel Execution for AI Brokers
Parallel Execution would not simply make workflows quicker—it makes AI brokers smarter and extra scalable. When brokers can concurrently collect, course of, and act on information from a number of sources, your complete automation pipeline turns into extra environment friendly.
It additionally helps cut back backend load and useful resource consumption by eliminating pointless wait instances. AI brokers that beforehand needed to “wait in line” to carry out duties can now function at their full potential, delivering real-time insights and actions throughout the enterprise.
How It Works in Kore.ai’s Device Builder
The Kore.ai Agent Platform now helps the creation of unbiased workflow branches inside its no-code Device Builder. Every department represents a job or motion that doesn’t depend on others. When Parallel Execution is enabled, AI brokers can provoke all these branches on the similar time.
As soon as all branches full, the platform intelligently converges the outcomes, enabling the agent to proceed with the following steps—whether or not that’s presenting data to a consumer, making a call, or triggering one other system motion. This type of execution logic is crucial for constructing highly effective, context-aware brokers that scale with enterprise complexity.
Why Parallel Execution is Essential for AI Workflow Automation
As enterprises scale their use of AI brokers throughout departments and workflows, velocity and effectivity are not nice-to-haves—they’re mission-critical. Whether or not it’s lowering wait instances in buyer help, accelerating onboarding processes in HR, or enabling speedy decision-making in operations, responsiveness is immediately tied to enterprise outcomes.
Parallel Execution addresses one of many largest friction factors in AI workflow automation: latency from sequential processing. By eliminating the factitious delays between steps, Parallel Execution ensures that AI brokers can function with the velocity and intelligence required in as we speak’s always-on, multi-system enterprise environments.
Right here’s why it issues:
- Actual-Time Responsiveness: In situations the place each second counts—like routing help tickets, dealing with fraud alerts, or processing gross sales inquiries—Parallel Execution helps brokers reply virtually immediately.
- Scalable Automation: As workflows develop extra complicated, with dozens of instruments and methods concerned, the flexibility to run duties concurrently ensures efficiency doesn’t degrade with complexity.
- Higher Person Expertise: Sooner brokers imply smoother, extra pure conversations and processes—resulting in greater satisfaction, engagement, and retention.
- Elevated Throughput: When brokers full duties quicker, you may deal with extra quantity with the identical infrastructure—lowering operational prices whereas growing capability.
In brief, Parallel Execution transforms AI brokers from job runners into clever orchestrators—able to navigating intricate enterprise ecosystems with velocity, context, and precision. It’s a foundational functionality for scaling AI-driven automation with out compromising efficiency or consumer expertise.
Need to see Parallel Execution in motion? Request a demo or discover how the Kore.ai Agent Platform can rework the way in which your AI brokers work.