How To Pick The Right Ai Agent Forbes

Bonisiwe Shabane

-Jan 27, 2026, 4:06 AM

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. 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 based on the categories, and monthly search volume, and share key takeaways. 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. Every executive I speak with wants to deploy AI agents in their business.

Yet most are making the same costly mistake: choosing the wrong tasks to automate. In my previous article, A Beginner’s Guide To Building AI Agents, I explained how to get started with agentic AI. Now it's time to tackle the most critical step: finding the right jobs to use them for. Get this wrong, and you'll waste time and money. Get it right, and you'll transform how your business operates. Agents are best thought of as autonomous AI assistants capable of carrying out far more complex and multi-step tasks than simpler ChatGPT-style chatbots.

Currently, the hottest topic in business technology is sometimes referred to as “virtual workers”. However, I’m cautious of this line of thinking for two reasons. Firstly, it implies that they can in some way replace humans. Secondly, I believe understanding how they’re different from human workers is critical to using them effectively and responsibly. So, they’re still tools, albeit very autonomous ones, and picking the right situations to use them is essential. There is no one-size fits all when it comes to AI agents in the workplace.

Image: Simon Kadula/Unsplash Agentic artificial intelligence (AI) is the latest transformative offshoot of AI’s generative capabilities. By 2028, 33% of enterprise software applications are predicted to include AI agents, enabling 15% of work decisions to be autonomous. Furthermore, up to 90% of businesses see agentic AI as a potential source of competitive advantage – gained through efficiency, enhanced decision making or scalability. Valued at $5.1 billion in 2024, the AI agent market is estimated to reach $47.1 billion by 2030. Agents are defined as autonomous systems that perceive their environment, process information and take actions to achieve specific goals.

But there’s a growing range of agentic models, with different capabilities, technologies and levels of human engagement. Artificial Intelligence (AI) has evolved from chatbots answering simple questions to intelligent agents that can take actions, make decisions, and work alongside people. Today, choosing the right AI agent is a key step for any business looking to improve productivity, reduce costs, and scale operations smartly. But with so many types and platforms available, how do you decide which one fits your needs? This guide breaks it down into a practical framework and a simple 5-point checklist to help you make the right choice. Before choosing a solution, it’s helpful to know the three common types of AI agents used in businesses today:

These agents handle repetitive tasks like lead scoring, report generation, or document validation. They work behind the scenes to improve speed and reduce manual effort using machine learning and logic-based rules. Use case: A sales team uses an AI agent to automatically prioritize leads and send alerts to reps for follow-up. AI agents are the hottest topic in technology right now. But those eager to experiment face an overwhelming maze of hype, conflicting ideas, competing platforms and tricky technical and ethical challenges. Over a series of articles, I’ll define the questions, practical steps and decisions that need to be addressed to embark on this journey.

Perhaps the most exciting aspect of agents is that although they represent bleeding-edge technology, they’re simple enough for anyone to understand and start working with. This means you don’t need to be an AI specialist, data scientist or software engineer to solve problems with AI, which just a few years ago would have taken some serious hard coding and... AI agents provide the opportunity to automate complex tasks and even entire workflows, but also raise important questions and critical risks, and I’ll cover all of this, too. Hiring the right people is everything. A good hire can work like a missing puzzle piece, boosting creativity and productivity throughout the whole team. A bad hire does the opposite—it can drain morale, kill motivation and drag everyone else down.

No leader ever sets out to make a bad hire, but sometimes, it happens anyway. We get swept away by a candidate’s on-paper credentials, charisma, or connections, ignoring the red flags that perhaps should have been obvious. The price of these errors are high—the Department of Labor estimates that a bad hire can cost a company as much as 30 percent of the employee’s first-year salary, and that’s not even including... Hiring, of course, begins with recruitment—the process of identifying, sourcing, screening, shortlisting and interviewing candidates. Historically, this has been an imperfect science. Candidates are identified in a handful of ways, none of them especially comprehensive or systematic.

Now, AI agents are refining the process, making the search for candidates both more thorough but also, critically, faster and more effective. And that spells big things for hiring managers’ ability to pick the right candidate. Here’s how.

How To Pick The Right Ai Agent Forbes

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