Build Together

Not long ago, the idea of a computer program that could autonomously handle complex tasks – almost like a virtual employee – sounded like science fiction. Now, these “AI agents” are one of the hottest topics in tech. So, what’s behind the hype? And more importantly, what can an AI agent actually do for your business? Let’s break it down in simple terms.

What Are AI Agents, Exactly?

At their core, AI agents are software programs powered by advanced AI (often large language models) that can take action towards a goal with minimal human guidance. Unlike a regular app that only does exactly what you explicitly program it to, an AI agent has a degree of autonomy – it can assess a situation, make decisions, and execute tasks in a continuous loop of perception and action. In practical terms, an AI agent can be thought of as a smart assistant that doesn’t just give you an answer and stop; instead, it can carry out a series of steps to solve a problem or complete a workflow.

Why all the hype now? A lot of it started in early 2023 when experiments like AutoGPT and BabyAGI burst onto the scene. These projects showed that by hooking up a powerful language AI (like GPT-4) to various tools (web browsing, databases, code execution, etc.), you could create an agent that iteratively plans and acts toward a goal you give it. For example, you might tell an agent, “Research the best camera for under $500 and prepare a report,” and the agent will autonomously generate search queries, sift through websites, compile information, maybe even draft a report – all without you intervening in each step. The tech community saw this and imagination caught fire: people dreamed up agents that could run businesses, handle customer service, manage your schedule, you name it. In fact, AutoGPT’s open-source project garnered over 100k GitHub stars almost overnight, a sign of huge excitement among developers.

Of course, reality is catching up with the hype gradually. Today’s AI agents are powerful but not magical. They sometimes get things wrong or stuck in loops (early AutoGPT versions famously could wander off-track). Think of them as really smart interns – they work fast and can figure out a lot on their own, but they still need oversight for important decisions. Even so, the capabilities are advancing quickly. Gartner predicts that by 2028, a third of enterprise software will have agentic AI under the hood, up from just 1% in 2024, and that a significant chunk of business decisions might be made autonomously by these agents. In short, AI agents are poised to become common in the coming years.

How AI Agents Can Help (Real Examples)

The general idea of an AI agent can sound abstract, so let’s look at concrete use cases already emerging. Many organizations are experimenting with AI agents in different roles, such as:

Customer service “virtual agents”: These are beyond the old school chatbots. Modern AI customer agents can understand complex questions and pull in information from various sources to resolve an issue. For instance, Uber uses AI agents to assist their customer support reps – the AI automatically summarizes customer inquiries and retrieves context from past interactions, so the human rep has a full picture instantly. This kind of agent acts like an omnipresent support sidekick, slashing the time it takes to help each customer and ensuring nothing falls through the cracks.
Personal assistant agents for employees: Imagine an AI that reads through your company’s knowledge bases, ticket system, and emails, and can answer questions like “What’s the status of Project X?” or “Schedule a meeting with the sales team next week.” Companies are deploying agents in tools like Slack or Microsoft Teams that employees can ask for help. A notable example is an AI assistant that helps with onboarding – new employees at some firms can ask an AI agent HR questions (“How do I set up my VPN?”) and get instant answers, instead of waiting for HR emails. In fact, businesses are building agents to explain pay and benefits, assist with training, schedule meetings, and more. It’s like each employee can have a personal HR or IT assistant on demand.
Sales and research agents: There are AI agents that can, say, automatically research prospective clients before a sales call – compiling recent news about their company, their industry trends, even scouring LinkedIn for the prospect’s background. By the time the sales rep sits down for the meeting, they have a tailored brief ready. Another example: some real estate firms are experimenting with agents that autonomously gather data on property listings, analyze market comps, and generate reports for clients, which used to be manual work.
Operations and IT agents: These are agents that keep an eye on systems and take actions. For instance, a simple IT agent might monitor a server’s health and automatically attempt fixes or call for backup if something goes wrong. In manufacturing, an AI agent might watch sensor data from equipment and decide when maintenance is needed (predictive maintenance) – essentially acting to schedule a repair before a machine breaks. Oracle’s recent report lists examples like agents that evaluate equipment repair options from photos, or plan optimal delivery routes based on real-time data. These agents handle multi-step tasks that cross different software systems (diagnosing an issue, then creating a support ticket or re-routing a delivery truck). They work tirelessly in the background to streamline operations.
Creative and code agents: On the creative side, there are agents that can generate design drafts or marketing content variations. On the engineering side, “code agents” can generate code, test it, debug, and iteratively improve it. For example, developers can specify a goal (“build a simple app that does X”) and a code agent will attempt to scaffold it out, call APIs, etc., while the developer supervises. We’re still in early innings here, but it’s a glimpse of how software development might speed up.

It’s important to note that while some of these capabilities have existed in separate tools, AI agents bring them to a new level by combining skills and working continuously. Traditional automation might handle a repetitive task A → B → C in a fixed way. An AI agent, by contrast, can handle unexpected detours: if step B returns an error, the agent can reason, try a different approach for B, or even do D instead, much like a human would adapt on the fly. That adaptability is game-changing.

Getting Started with AI Agents in Your Business

If you’re thinking this sounds great but also complex to implement, you’re not alone. The good news is, you don’t necessarily need a huge budget or a team of PhDs to start using AI agents. Here are some approachable ways to dip your toes in:

Leverage existing platforms: Many software providers are baking agent-like AI features into products you might already use. For example, certain CRM systems now have AI that will proactively remind you “You haven’t followed up with Client Y in 2 weeks, shall I draft an email?” – that’s an agent at work. If you use project management or helpdesk software, check if they’ve introduced AI automation features (many have). Starting with these out-of-the-box agents can deliver quick wins.
Start with a narrow use case: Identify one tedious workflow in your business – maybe it’s generating a weekly report, or handling a common customer request. Then explore if an AI agent tool or service exists for that (chances are, it does). By solving one concrete problem, you’ll learn how the agent behaves and build confidence. For instance, a small online retailer might set up an AI agent to automatically flag and respond to simple customer emails (returns, shipping questions) each morning. With that working, you could then broaden its duties.
Keep a human in the loop initially: As amazing as AI agents are, they can occasionally err. When you first implement one, have an employee supervise its outputs. Treat it like a trainee: it learns from feedback. For example, if you deploy an agent to draft social media posts, have your marketer review and tweak its posts at first. Over time, you might trust it with more autonomy once it proves itself. Almost all successful uses of agents right now involve this human-AI collaboration phase.
Mind the ethical and data considerations: If an agent is pulling data or making decisions, ensure it’s respecting privacy and compliance rules. Also, communicate to your team (or customers if relevant) that you’re using an AI agent in the loop. Transparency helps build trust. You don’t want employees thinking a “ghost in the machine” is making decisions without oversight – make it clear it’s a tool they control, not vice versa.

We’re still early in the AI agent journey, but the trajectory is exciting. Businesses that effectively use these agents stand to gain a competitive edge – imagine having a tireless team of digital helpers handling the nitty-gritty while your human team focuses on big-picture innovation and relationships. Companies like Uber, Toyota, and others are already saving thousands of work-hours and improving productivity by deploying internal AI agents. And it’s not just large enterprises – the playing field is quite level here, because many AI agent tools are available via cloud services to even the smallest startups.

The Bottom Line (and an Invitation)

AI agents are hyped for good reason: they represent a leap from static automation to adaptive, intelligent automation. For businesses, this could mean doing more with less, responding faster to customers, and unlocking new capabilities that previously required more manpower or expertise than you had. But you don’t have to navigate this alone or jump in blindly.

At Build Together, we’ve been following the AI agent trend closely and experimenting with what works best in real-world scenarios. We can help you brainstorm and even build a pilot AI agent for your specific needs – at no initial cost to explore. Whether it’s an agent to handle your marketing research, an internal chatbot for your team, or something totally out-of-the-box, we love helping businesses innovate with these technologies. The key is to start small but smart, learn, and grow. AI agents might be the new kids on the tech block, but with the right approach, they could soon be the most reliable “employees” you’ve ever had – working tirelessly in the background while you focus on what you do best.

(Interested in what an AI agent could do for you? Feel free to reach out – at Build Together, we’re always happy to discuss ideas and help you take the first step into the future.)