AI Agents are computer programs (or software) that have a certain amount of autonomy to perform predetermined tasks. They have, so to speak, a degree of agency. That amount of agency is largely determined by the AI's instruction and implementation, often with oversight. AI Agents are generally applied to areas where flexibility allows the agent to better deliver on a task or need.
Think of a chatbot for an e-commerce platform. Ideally, you want the chatbot to be able to handle a customer's requests, which can be wide-ranging. It may be questions about the product ("How tall is the back of this chair?") with particular language nuance ("Show me shoes for a Christmas party"), about returns ("The color didn't match the picture online"), or help navigation ("where can I find my subscription settings?"). There are edge cases and language considerations in the almost infinite amount of requests a customer can make, which means that flexibility improves the user experience.
It's still early days, so we shouldn't over-extrapolate today's functionality with tomorrow's projections, but initial indications suggest that workflows that traditionally were protected from automation given the inability of programmed logic to handle edge cases, are vulnerable to AI Agents. These include areas such as call centers, customer service, and basic tech support.
For higher-skilled work, AI Agents are largely being developed as complements, aimed at driving productivity enhancement. They can leverage their wider autonomy to find commonly repeated patterns in workers' daily tasks or workflows, allowing machines to help reduce those redundancies, so humans can focus more on higher-order, creative work.
At ModuleQ, we think AI Agents can transform the quality of work in much the same way that ATMs transformed the nature of the bank teller role. While there were fears that tellers would become redundant with these magic boxes that could fulfill customer's deposit and withdrawal needs, we in fact saw bank tellers transform into customer service and sales-focused roles, where human-to-human interaction became the focus in helping banks develop their customer relationships. Shockingly, the job of bank teller was not "disrupted" by automation; it was improved. It is ModuleQ's vision to do so with knowledge work.
ModuleQ's Unprompted AI is an Agent which pushes insight to knowledge workers, directly into their communications hub of choice. By combing through their repositories of data and information (including CRMs, internal research repositories, workspace terminals, and 3rd party research), Unprompted AI reduces search costs, increases ROI on existing data spend, and breaks through data silos. This is our way of delivering AI Agents to improve the quality and productivity of knowledge work.
AWS: "An artificial intelligence (AI) agent is a software program that can interact with its environment, collect data, and use the data to perform self-determined tasks to meet predetermined goals. Humans set goals, but an AI agent independently chooses the best actions it needs to perform to achieve those goals."
IBM: "An artificial intelligence (AI) agent refers to a system or program that is capable of autonomously performing tasks on behalf of a user or another system by designing its workflow and utilizing available tools."
Microsoft: "AI agents are designed to perform specific tasks, answer questions, and automate processes for users. These agents vary widely in complexity. They range from simple chatbots to copilots, to advanced AI assistants in the form of digital or robotic systems that can run complex workflows autonomously."