AI agents build on the experience of AI chatbots or AI assistants, taking it several steps further by carrying out actions for you using their own reasoning and inference, as opposed to step-by-step, prompted instructions. To illustrate this idea, LaMoreaux used an example of getting an AI assistant versus an agent to help you make a reservation at a restaurant.

In this example, if you ask an AI assistant to schedule a dinner at a restaurant, it may be able to make the reservation and even take it a step further by sending out an invite to the people on the reservation. However, it can't use additional context to go off-script and adjust accordingly.

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LaMoreaux explained that an AI agent would perhaps be able to pull information from your schedule, see that your panel was ending at 7 p.m., understand it takes you 20 minutes to get to the restaurant, and adjust accordingly, making the reservation for 7:20 p.m. Additionally, it may see that your first restaurant is unavailable then, so it will book the second one instead -- emphasizing its ability to perform actions unprompted.

"This idea of doing things in programmatic ways that can have multiple variations in them, I think, is the difference between assistants and agents," added LaMoreaux.

The most obvious benefit of incorporating an AI agent into an organization is that it frees time from employees' workloads by tackling tasks that are more tedious and administrative in nature, such as HR and backend processes. Employees can then redirect that time gained toward higher-level tasks that humans do best.

"For every minute that someone spends in an HR process -- transferring an employee, requesting time off, looking up your 401(k) balance, thinking about what classes you need to take, analyzing raises -- for every minute you spend on one of those internal processes, it is a person who is not out meeting with a client, it is a minute you are not building a product, a minute you are not being creative," said LaMoreaux.

The benefits of saving time are easily apparent -- and we all know time is money -- but an often overlooked benefit lies in AI agents' orchestration element. This orchestration role refers to how AI agents coordinate with various underlying tools to perform tasks and deliver outcomes efficiently.

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For example, if you wanted to book a trip, hypothetically, an agent would be able to look at different applications, such as your calendar to see when you are free, the airline's app to book the flight, a hotel app to book your stay, and your email to draft a message to your boss saying you will be out of the office. The ability to piece all of these elements together is a crucial aspect of the value AI agents bring to corporations.

With so many tools on the market, LaMoreaux says that it is often difficult for employees to discern which tools to use, even if they think the idea itself is great. Moreover, at IBM last year, 50% of employees and managers never logged into an HR system despite it being home to close to a hundred HR tools because of that dilemma.

"Don't underestimate this orchestration point, and for many employees and many companies, they have AI tool overload," added LaMoreaux. "What this agent does -- this orchestration layer -- allows employees and managers to go into one place and interact with all of those underlying tools."

Ever since generative AI exploded in popularity, one of the major concerns has been how it will impact jobs and replace the human workforce. That fear is only heightened with the mention of AI agents, as they can carry out tasks for humans without even needing constant human prompting or supervision, eliminating the need for humans to perform specific tasks even further.

However, just because an AI agent can carry out some tasks doesn't necessarily mean it can do all of them. As mentioned above, there are critical business operations that an AI agent cannot replace, such as face-to-face interactions with clients or higher-level tasks involving problem-solving, experience, or creativity.

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In fact, according to LaMoreaux, AI agents may amplify the need for humans in some areas.

"With AI and generative AI, domain expertise becomes more important, not less important," said LaMoreaux. "The AI agents already know the basics, so when things need to get unique, then routed to humans, it's going to be higher-order questions and problems."

Building on this idea, Elsakr also highlighted that the models themselves don't have ideas. As a result, it is imperative that humans come up with better ideas now and spend real time implementing ideas that matter.

Another concern about AI agents is that they are entirely autonomous and, as a result, can handle important business tasks and data without the need for direct human supervision guiding their every step, leaving room for bias, privacy concerns, and error.

However, it is important to remember that AI agents can be tailored to fit the specific company's needs. They are given the authority to access only information the company is willing to share and can only perform actions they are specifically granted the authority to do. Ultimately, these tasks should be carefully chosen to ensure they align with the company's needs and values.

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For example, LaMoreaux explained IBM uses an agent to help match candidates to potential job roles, as opposed to using an AI agent for selection to weed out applications. Even though other companies use AI agents for filtering and selecting processes, there is a risk of inviting AI bias and not selecting people with different educational backgrounds, which doesn't align with the company culture.

This keeps the company in control of how AI agents behave. As a result, even though the technology is autonomous, users can find comfort in knowing it won't act in ways it hasn't been permitted to. 

Even though some business leaders are hesitant to implement the technology and take a wait-and-see approach to how AI agents perform for other companies, both panelists agreed that the time to get started is now.

"You cannot wait. The only employees that are going to be replaced are the ones that aren't using AI; the only companies that will be are the ones that aren't using AI," said LaMoreaux.

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At the individual level, even if business leaders are slow to implement the technology, people should familiarize themselves with it and seize the opportunity to begin learning how to best implement and understand it.

Unlike the internet or search, which had a longer runway before becoming a cornerstone of business operations, AI has exploded at a much quicker pace and is causing a "tectonic shift," according to Ekstar. As a result, the best time to start the upskilling process is now.

"You don't have a choice on this one; what I encourage people to do, making sure your CTO greenlights the tool, is you have to lean into this at this point and upskill yourself," said Ekstar.