AI brokers are quickly changing into the driving pressure behind clever enterprise workflow automationfrom processing buyer inquiries to orchestrating multi-step enterprise processes with multi-agent orchestration. However as these AI brokers tackle extra obligations, their efficiency turns into tightly coupled with how briskly they’ll retrieve and act on knowledge throughout enterprise methods.
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 a substitute of executing every step in sequence. The outcome? Sooner, smarter, and extra environment friendly brokers that reply in actual timeand at enterprise scale.
The Drawback with Sequential Execution
Earlier than Parallel Execution, AI brokers have been restricted by a sequential activity mannequin. Let’s say an agent must fetch details about a userbasic profile particulars from Salesforce, buy historical past out of your CRM, and assist tickets from a helpdesk system. Within the conventional workflow design, the agent could be pressured 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 subsequent 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 inputlike a consumer IDis accessible, the agent can leverage instruments to set off simultaneous knowledge fetches from a number of methods with out ready for one to finish earlier than beginning the subsequent.
As a result of these methods (e.g., Salesforce, CRM, and helpdesk) function independently and haven’t 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 knowledge in simply 5–6 seconds on commonthe time it takes for the longest of the parallel requests to resolve.
This elementary shift in execution dramatically boosts the efficiency of AI brokers. They not solely retrieve data quicker but in addition act on it extra shortly, resulting in smarter choices and extra fluid conversations or processes. It’s not simply fasterit’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 assist. To be efficient, the agent should perceive the shopper’s present standing, current purchases, and historic interactionsdata that lives throughout a number of backend methods.
With Parallel Execution, the agent immediately dispatches three parallel knowledge requestsone to Salesforce for contact information, one other to the CRM for transaction historical past, and a 3rd to the helpdesk database for assist logs. Inside 5 seconds, the agent receives and synthesizes a full buyer profile, permitting it to answer the consumer shortly and precisely.
In distinction, a standard agent working with sequential execution would take 3 times longer to collect the identical informationdelaying the response, degrading the consumer expertise, and doubtlessly inflicting drop-off or frustration.
Parallel Execution unlocks a brand new degree of responsiveness, empowering AI brokers to ship quick, personalised, and context-aware interactionswhether 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 fasterit makes AI brokers smarter and extra scalable. When brokers can concurrently collect, course of, and act on knowledge from a number of sources, your complete automation pipeline turns into extra environment friendly.
It additionally helps scale 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 unbiased workflow branches inside its no-code Instrument Builder. Every department represents a activity 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 subsequent stepswhether that’s presenting data to a consumer, making a call, or triggering one other system motion. This type of execution logic is important for constructing highly effective, context-aware brokers that scale with enterprise complexity.
Why Parallel Execution is Crucial for AI Workflow Automation
As enterprises scale their use of AI brokers throughout departments and workflows, pace and effectivity are now not nice-to-havesthey’re mission-critical. Whether or not it’s lowering wait instances in buyer assist, 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 pace and intelligence required in immediately’s always-on, multi-system enterprise environments.
Right here’s why it issues:
- Actual-Time Responsiveness: In eventualities the place each second countslike routing assist tickets, dealing with fraud alerts, or processing gross sales inquiriesParallel Execution helps brokers reply virtually immediately.
- Scalable Automation: As workflows develop extra complicated, with dozens of instruments and methods concerned, the power to run duties concurrently ensures efficiency doesn’t degrade with complexity.
- Higher Consumer Expertise: Sooner brokers imply smoother, extra pure conversations and processesleading to larger satisfaction, engagement, and retention.
- Elevated Throughput: When brokers full duties quicker, you may deal with extra quantity with the identical infrastructurereducing operational prices whereas growing capability.
Briefly, Parallel Execution transforms AI brokers from activity runners into clever orchestratorscapable of navigating intricate enterprise ecosystems with pace, 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 remodel the best way your AI brokers work.
