How To Pick The Right AI Agent

If generative AI was the first frontier in artificial intelligence, AI agents are the next. We’ve reached a point where startups are posting job listings—not for humans, but for AI agents (or those who build them). It might be a clever PR move, but it’s not a gimmick. AI agents are becoming integral to forward-thinking organizations.

But what exactly is an AI agent?

Put simply, it’s software that autonomously makes decisions, takes actions, and interacts with others—without human input. It executes multi-step goals, adapting along the way. At Jotform, an online form company with an automation-first mindset, we’re closely tracking these advances. In fact, we’re rolling out our own AI agents to help users streamline business processes, enhance customer experiences, and save time and money.

Today, AI agents fall into three main categories: Automation Agents, Conversational Agents, and Multi-Agent Platforms. Below, I’ll break down each type, highlight the top 50 agents in each category (based on monthly search volume), and share key takeaways.

Automation AI Agents

Imagine a sales team at a scrappy software startup. The team wants to automate its lead scoring process to focus on the most promising prospective users. When a new batch of leads rolls in, an AI agent evaluates them based on the team’s predefined criteria—engagement level, company size, previous interactions, etc. Next, the agent compares the leads and prioritizes the ones with the highest potential. Finally, the agent sends an email rounding up the top prospects to the sales reps, and then the team quickly follows up.

As the above example demonstrates, Automation Agents perform tasks, processes, and workflows, like lead scoring, with minimal or no human intervention. They do this using machine learning, predictive analytics, and rule-based logic.

Automation Agents excel in areas like content creation, supply chain management, and software testing—handling data processing, context-sensitive decision-making, and task execution. By minimizing manual effort and boosting efficiency, these agents help organizations improve productivity, slash human errors, and ultimately, lower their operational costs.

Conversational AI Agents

A fledgling e-commerce company wants to improve its customer support. Rather than pushing human customer service reps to work longer hours, the company builds a Conversational Agent into its website. When a customer asks a question—such as order status or return policy—the agent responds immediately using natural language processing. The agent can guide users through troubleshooting, provide tailored recommendations, and redirect complex issues to human representatives. This allows the support team to focus on higher-impact activities without giving short shrift to everyday customer concerns.

This is the essence of a Conversational Agent. They’re designed to interact with people in a socially intelligent manner. Using natural language processing, machine learning, and behavioral modeling, they detect tone, intent, and context to generate human-sounding, accurate responses.

Across industries, businesses are deploying these agents in customer service chatbots, virtual assistants, and collaborative robots (cobots). They enhance user experiences, facilitate teamwork in both virtual and physical environments, and build trust through responsive, context-aware interactions.

Multi-Agent Platforms

Let’s say an e-commerce company wants to automate its order fulfillment process. Instead of having human employees spend valuable time manually coordinating between different apps, the company sets up a Multi-Agent Platform, wherein specialized AI agents can work together with little to no human input. When a customer order rolls in, the order processing agent retrieves order details from Shopify and verifies the payment in Stripe. Next, the inventory management agent checks the stock in Airtable. If an item is low in stock, it triggers a reorder request. Once an order is confirmed, the shipping and tracking agent generates a shipping label using ShipStation and sends tracking details to the customer via Gmail. And so on…

As the above example shows, Multi-Agent Platforms combine AI agents with different specialties to achieve certain goals. They use machine learning, natural language processing, and adaptive reasoning to facilitate teamwork, communication, and decision-making. Multi-Platform Agents are truly impressive in their capacity to coordinate with other AI agents—offering suggestions, sharing insights, and taking action, with zero human oversight. These agents are making waves in sales, marketing, and customer support.

AI Agent Takeaways

The benefits of AI agents are pretty clear. They boost efficiency and productivity. They enhance decision-making. They’re available around the clock. They make customers feel they’re receiving personalized attention. They help organizations cut costs. And big picture, by boosting efficiency, they leave humans more time and space to do their best thinking—the kind that leads to innovation.

The above data, however, has a few important takeaways, beyond the mere proliferation of AI agents. Here they are.

Growing Interest In Automation Across Industries

While AI agents represent the cutting edge of technology, their impact extends far beyond the tech industry. Businesses across sectors are rapidly adopting automation through AI agents to streamline repetitive tasks and boost efficiency.

This trend is particularly strong in e-commerce, marketing, and customer service, where applications like Reworkd and ChatGPT Tasks are freeing employees from tedious manual work. This shift allows them to focus on high-impact activities, such as developing strategic initiatives that can move the needle for an organization.

Demand For Enhanced Customer Interactions

Effective communication is increasingly critical for customer satisfaction. This means that company responses must be immediate, accurate, and personalized. If a customer has a midnight emergency on Saturday, someone better be on-call to help them—or something, like an AI agent.

AI agents are becoming essential tools for enhancing customer interactions, particularly in retail, healthcare, and finance. Solutions like Agentforce and Leena AI provide human-like interactions, which may seem counterintuitive at first—how can AI enhance personalization? Agents help organizations provide tailored information 24/7, allowing human employees to focus on more complex issues. Ultimately, agents are improving the overall customer experience.

Versatility Of Multi-Agent Platforms

Multi-Agent Platforms are revolutionizing the approach to workflows in ever more complex business landscapes. Organizations across industries are leveraging these platforms to automate cross-functional processes, enhance collaboration across silos, and improve decision-making. As businesses integrate more processes into these platforms, their benefits will only compound.

Applications like Make and Magical exemplify the benefits of these platforms, reclaiming significant amounts of time and energy lost to procedural inefficiencies—such as bottlenecks, miscommunication, and human error.

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While the future of AI is anything but clear, it’s safe to say that agents will continue to evolve and integrate into various sectors. They’re no longer just tools for convenience, but rather, partners in enhancing organizational effectiveness, productivity, and innovation. It’s no wonder savvy startups are looking to hire them.