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What is an AI Agent and How Businesses Use Them Today

Contributing Author

10 min read

Sep 1, 2025

TL;DR AI agents don’t just answer questions — they act. From processing refunds to resolving tickets, they free teams for complex work. The big question is how quickly you’ll put them to use.

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Picture this: your inbox is overflowing. A hundred support tickets arrived overnight. Password resets, shipping questions, refund requests. Your team hasn’t even logged in yet, but customers already expect answers.

Now imagine half of those tickets are resolved before anyone touches the queue. Refunds issued. Accounts updated. Tracking links sent. Not by a person clicking through screens, but by software that knows what to do.

That’s the promise of AI agents.

AI agents aren’t just chatbots with nicer language. They’re digital workers — autonomous programs that can understand context, make decisions, and complete tasks. In this piece, I’ll unpack what an AI agent really is, how it’s different from old-school automation, and why companies are betting big on them today.

The pressure pushing AI agents forward

Support leaders are feeling the squeeze. Customer expectations keep climbing: instant answers, personalized service, every channel open at all hours. Meanwhile, budgets and headcount aren’t keeping pace.

The old playbook — hire more agents, add more scripts — doesn’t scale anymore. Manual work means slower replies, longer queues, and burned-out teams. Chatbots helped for a while, but customers quickly spotted their limits.

This is where AI agents come in. Instead of waiting for instructions, they act. They can pull a policy, check an order, process a refund, or escalate when it’s too complex. That shift — from answering to doing — is why AI agents matter right now.

What is an AI agent

At its core, an AI agent is software that can act on its own. Instead of waiting for a human to click a button or follow a script, it takes in information, decides what to do, and carries it out. Think of it less as a chatbot and more as a digital co-worker.

Every AI agent has three moving parts:

• Perception – it reads inputs, whether that’s a customer message, a database, or a live system feed.

• Reasoning – it interprets the context and weighs options. Should it fetch a policy? Escalate to an agent? Trigger a workflow?

• Action – it executes the next step: sending a refund, replying to the customer, or updating an account.

This is where AI agents break from traditional automation. Old tools followed rules: if this, then that. Chatbots often did the same, delivering pre-written answers in a friendlier interface. AI agents are different. They adapt. They can learn from your company’s data, adjust to customer history, and know when to stop and hand off to a human.

That ability to blend autonomy with judgment is what makes them more than just another automation layer.

AI agents vs chatbots vs automation

It’s easy to confuse AI agents with the tools that came before them. On the surface, they all promise faster answers and lighter workloads. But the way they work — and the results they deliver — are very different.

• Chatbots are scripts in a chat window. They follow pre-set rules: “If a customer asks about shipping, show the FAQ link.” They can deflect a few questions, but they break when the request falls outside the script.

• Automation runs in the background. Think of ticket routing, auto-tagging, or an email autoresponder. It saves clicks, but it doesn’t understand context.

• AI agents sit in the middle — and beyond. They read what’s happening, decide the best next step, and act. Instead of only answering “What’s my order status?” they can actually look up the order, check the status, and send the update.

Take customer service as an example. A chatbot might tell you where to find a return form. An automation flow might create a ticket and assign it to the right team. An AI agent, like the ones in the Text App, can go further: it processes the return itself and issues the label instantly.

That leap — from answering to acting — is what sets AI agents apart.

Real-world applications

AI agents aren’t theory anymore — they’re showing up in daily work across industries.

In customer service, they take on the bulk of routine tickets: password resets, order tracking, refunds. With the Text App, this isn’t an add-on but the foundation. Its AI agents, powered by Text Intelligence, can scan a customer’s history, check against policy, and issue a return label in seconds. One retail support manager told us they cut their weekend backlog by half after turning on Text Intelligence. By Monday morning, agents were starting fresh instead of digging out.

In sales and marketing, AI agents qualify leads and schedule demos while your reps focus on closing. Instead of a static sequence of emails, they can send the right nudge at the right time, adapting to how a prospect behaves on your site.

In IT and operations, they act as silent monitors, fixing small problems before they reach humans. If a system shows repeated login failures, an AI agent can reset access or flag security risks instantly — no ticket required.

And for personal productivity, we see them as copilots: summarizing reports, drafting replies, or managing calendars. Instead of waiting for commands, they anticipate the next step and help move work along.

What makes Text different is its AI-first design. Many tools tack on bots as an afterthought. The Text App bakes agents into live chat, ticketing, and workflows. That means the automation feels natural: agents step in when context is clear, and people take over when empathy or complexity is needed. It’s not “bot or human.” It’s both, working together.

Framework for evaluating AI agents

Not every AI agent is built the same. Some are little more than upgraded chatbots. Others can plug into your systems and actually get work done. Before you commit, here’s a simple checklist to cut through the noise:

• Is it trained on your own data? Accuracy depends on context. An agent that only knows generic FAQs won’t solve your real problems.

• Can it act, not just answer? Look for tools that can process a refund, update an account, or trigger workflows — not just hand you a link.

• Does it know when to escalate? The best AI agents don’t fake confidence. They hand over to a human when empathy or complexity is needed.

• Does it unify channels and data? Switching between chat, email, and social without shared context is a recipe for frustration. A strong agent works across all of them.

• Is it adaptable as you grow? What works for a five-person team should also scale to hundreds without losing quality.

In practice, this is where the Text App, powered by Text Intelligence, stands out. Because the agents are embedded in a unified workspace, they don’t just answer on chat and disappear. They pull from your knowledge hub, act across tickets and conversations, and keep the history intact no matter where the customer shows up.

This framework helps you separate the buzzwords from the tools that actually lighten your team’s workload.

Benefits and trade-offs

The appeal of AI agents is obvious once you see them in action.

The benefits:

• Speed. Customers get answers in seconds, not hours. A refund processed at midnight feels effortless compared to waiting until the next shift.

• Scalability. When ticket volume doubles, AI agents don’t burn out — they just keep working.

• Lower workload. Your team can focus on complex, high-value conversations instead of endless password resets.

• Consistency. Answers come from the same knowledge hub every time, so customers don’t get mixed messages.

• Availability. Support doesn’t clock out. AI agents are live 24/7, across time zones.

But there are trade-offs to consider:

• Data quality. An agent is only as smart as the knowledge you feed it. Outdated docs equal outdated answers.

• Oversight. Even the best agents need a safety net — humans who can step in when nuance or empathy is required.

• Transparency. Customers should know when they’re talking to an AI. Trust erodes quickly if they feel tricked.

The balance matters. In the Text App, for example, Text Intelligence-powered agents handle routine tasks autonomously but hand off gracefully when a customer’s tone signals frustration or when a request falls outside the rules. That design prevents the “bot wall” customers hate and keeps teams in control.

Used thoughtfully, AI agents don’t replace humans — they make the human work more valuable.

The real signs of success with AI agents

You know an AI agent is working when the numbers — and the team — tell the same story.

With the Text App, companies often see weekend backlogs vanish. Support leaders report that Text Intelligence agents handle up to half of repetitive requests automatically, leaving human agents free to focus on high-stakes conversations. The outcome: faster replies, happier customers, and less burnout on Monday mornings.

Competitors are making similar moves. Zendesk’s Answer Bot can deflect common questions, though it still leans on structured ticketing. Intercom’s Fin AI agent is praised for its conversational tone, resolving about half of incoming chats before they reach an agent. Freshdesk’s Freddy AI routes tickets and suggests replies, cutting handling times for small teams on tight budgets.

But true success isn’t measured only in deflection rates. It shows up in:

• Customer satisfaction scores that stay high even when volume spikes.

• Agent morale when they log in and see meaningful work, not repetitive drudgery.

• Leadership confidence knowing support can scale without a proportional headcount increase.

Text stands out because AI isn’t a plug-in bolted on later — it’s built into the core. That design makes automation feel seamless, not forced. Success, in this case, looks like customers who never notice the handoff between agent and AI because the experience is smooth all the way through.

The future belongs to AI agents

AI agents aren’t just a new name for chatbots. They represent a real shift: from answering questions to completing tasks. That shift matters because it changes how teams work. Instead of drowning in routine requests, people can focus on the conversations that need empathy, judgment, or creativity.

The companies finding success aren’t chasing trends. They’re choosing tools where AI and humans work together in one flow. That’s the difference between a frustrated customer stuck in a bot loop and one who gets what they need in seconds.

AI agents are here, and they’re only getting smarter. The question now isn’t if you’ll use them — it’s how quickly you’ll put them to work.

Ready to see AI agents in action?

The fastest way to understand the difference is to try it yourself. With the Text App, you can set up AI agents powered by Text Intelligence in minutes — no complex build, no long onboarding.

👉 Start free trial

FAQ

What is an AI agent?

An AI agent is software that can act on its own — reading context, making decisions, and completing tasks like processing refunds or updating accounts.

How is an AI agent different from a chatbot?

Chatbots give scripted answers. AI agents go further: they act. They can pull data, trigger workflows, and know when to escalate to a human.

Can AI agents replace human support teams?

No. They’re best used alongside people. Agents handle repetitive tasks, while humans bring empathy and judgment to complex cases.

Are AI agents safe to use with customer data?

Yes, if implemented correctly. In platforms like the Text App, AI agents are trained on your company’s own data with clear safeguards for privacy.

What can AI agents do beyond customer service?

They’re used in sales, IT, and operations — from qualifying leads to monitoring systems and automating fixes.