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What are AI agents? That is the question that many are talking about as companies increasingly consider rapidly evolving AI developments in the context of the workplace.
AI companies are highlighting the possibilities of AI agents, and considering the continuous updates to the AI industry, including AI agentic technology, the concept is now becoming much more conceivable in certain industries.
But what are AI agents? Here, we will break down everything you need to know about what AI agents are, why they’re becoming increasingly popular, and review concerns or limitations around the technology.
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First, let’s start by defining what we mean by the term ‘AI Agent.’
Google defines AI agents as, a software system. The system uses AI (artificial intelligence) to conduct tasks for users.
In concept, it’s similar to the LLMs (large language models) that many are now familiar with, however, there are some differences.
As Forbes notes, an AI agent is different from an LLM like ChatGPT because ChatGPT needs a human to input instructions or a prompt to produce a result.
That’s why, as Microsoft notes, what makes AI agents stand out is their reasoning and learning capabilities because these typically enable AI agents (depending on the model or type) to “run complex workflows autonomously” or independently.
In their guide, Microsoft further notes that AI agents are typically capable of:
IBM notes that this makes AI agents a popular choice for tasks such as virtual assistance or customer service.
Recently OpenAI released Operator, an AI agent that is available through a research preview. In particular, it’s a computer-using agent (CUA). This gives it the ability to click buttons on a web page, type, or scroll.
One of the top reasons that AI agents are gaining interest is their cost-saving potential. AI agents are designed to automate mundane tasks, speed up processes, and reduce costs, which could result in improved profit margins for businesses. However, Forbes notes that due to the level of capital they require to deploy, initially, they may be cost-intensive.
Then, their potential application for customer service also makes them an intriguing option to support human teams. With the ability to have an automated assistant, businesses could potentially enhance user experience and offer a more seamless and personalized experience.
Take an example of an eCommerce site. Rather than waiting up to 24 or 48 hours to get a response from busy support staff, a customer could receive answers rapidly, in an instant conversation with an AI agent, streamlining the experience.
Then, if additional support was required, the human customer service representative could step in to answer or clarify any remaining questions.
However, there are concerns and limitations around AI agents that are important to keep in mind.
One of the first concerns is the potential for AI agents to impact the workforce and jobs.
Forbes notes that some jobs could be impacted, others may incorporate the tech as a support to boost staff productivity, and that it may also lead to new jobs opening up, “leaders can instead choose to position the technology as a tool for accelerating market growth or super augmenting your most valuable asset—your people.”
Going back to our eCommerce example, if a company deploys AI agents for customer support, then, the job of the human who once sent email responses may adapt and change (for instance it may focus on reviewing the AI agent's replies to customers) and incorporate the new tech. However, as AI agents are rapidly developing time will tell the full impact.
There is also a concern regarding potential bias or unfair outcomes. If a model is trained on a specific set of data, then it may produce inaccurate answers or biased outputs.
Amazon Web Services, notes that due to this limitation, it’s important to keep a human in the loop as a safety measure to ensure that the outputs are factual and fair.
This can also help to address concerns in a customer experience context, as a human customer service agent would still be available to review the AI agent’s responses and ensure they were in line with company policies.
After all, AI has been known to hallucinate (or present false information as fact) in a number of cases. Read more in our guide on AI hallucinations.
In addition to the potential for inaccurate outputs, other limitations of AI agents include access to technical resources for training and data privacy concerns. So, it’s essential to ensure that if AI agents are incorporated into workflows that proper data security measures are implemented.
However, there is cause to be positive about the future of AI Agents. If handled correctly and transparently, AI Agents could free up time for people to work on the tasks they excel at, while AI agents work hard in the background, streamlining manual tasks.
Although time will tell the complete impact of AI agents, one thing is for sure, transparency and clarity are absolutely crucial in the coming weeks, months, and years.
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