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 tasks, their efficiency turns into tightly coupled with how briskly they will retrieve and act on information throughout enterprise programs.
That’s why Parallel Execution is a game-changer. Launched within the Kore.ai Agent Platform’s Instrument Builder, this functionality permits AI brokers to carry out a number of duties concurrently with instruments, as an alternative 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 Downside 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—fundamental 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 could be compelled to attend for the primary fetch to finish earlier than beginning the second, and so forth.
Every step may 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 impartial duties concurrently. As quickly because the required enter—like a consumer ID—is obtainable, the agent can leverage instruments to set off simultaneous information fetches from a number of programs with out ready for one to finish earlier than beginning the following.
As a result of these programs (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 mandatory 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 sooner but additionally act on it extra rapidly, resulting in smarter choices and extra fluid conversations or processes. It’s not simply sooner—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 programs.
With Parallel Execution, the agent immediately dispatches three parallel information requests—one to Salesforce for contact data, 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 collect the identical data—delaying the response, degrading the consumer expertise, and doubtlessly inflicting drop-off or frustration.
Parallel Execution unlocks a brand new stage 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 sooner—it makes AI brokers smarter and extra scalable. When brokers can concurrently collect, course of, and act on information from a number of sources, all the 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 Instrument Builder
The Kore.ai Agent Platform now helps the creation of impartial workflow branches inside its no-code Instrument 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 choice, or triggering one other system motion. This sort of execution logic is important for constructing highly effective, context-aware brokers that scale with enterprise complexity.
Why Parallel Execution is Important 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 fast decision-making in operations, responsiveness is immediately tied to enterprise outcomes.
Parallel Execution addresses one of many greatest friction factors in AI workflow automation: latency from sequential processing. By eliminating the substitute delays between steps, Parallel Execution ensures that AI brokers can function with the velocity and intelligence required in at present’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 advanced, with dozens of instruments and programs concerned, the flexibility to run duties concurrently ensures efficiency doesn’t degrade with complexity.
- Higher Consumer Expertise: Sooner brokers imply smoother, extra pure conversations and processes—resulting in increased satisfaction, engagement, and retention.
- Elevated Throughput: When brokers full duties sooner, you’ll be able to 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.
Wish to see Parallel Execution in motion? Request a demo or discover how the Kore.ai Agent Platform can remodel the way in which your AI brokers work.
