What Are AI Agents Capable Of?

What are AI Agents Capable Of, and What Characteristics Enable These Capabilities?

According to Gartner:
"AI agents are autonomous or semi-autonomous software entities that use AI techniques to perceive, make decisions, take actions, and achieve goals in their digital or physical environment."

But let’s cut to why this actually matters to you.

Autonomy: Transforming Day-to-Day Work

The reality is that your day-to-day work is about to change dramatically—and not in some distant future, but in the near term. Think days or weeks, not decades.

AI-driven workflows, powered by AI agents, are becoming the norm, fueled by innovations from startups and tech giants alike. Imagine the leap from paper to computers or from computers to the internet—that’s the scale of transformation AI agents bring.

Let’s Make This Clear:

AI agents can act as operators for your current workflows. All those endless copy-pastes, button clicks, mouse wiggles, and keystrokes that kick off tasks? AI can handle them seamlessly.

But it’s not just about repetitive automation. AI agents bring adaptive learning into the mix. They don’t just follow static scripts—they learn from context, remember past tasks, and get better over time.

Example:

• The sales forecast your team uses for decision-making differs from the one you share with Wall Street.
• Your procurement workflow doesn’t operate the same way as your internal inventory management.

AI agents can adapt to these contextual differences, ensuring they perform tasks with precision and nuance.

If you’re curious about the deeper complexities of how these tools work, check out this insightful article by Anthropic:
Building Effective Agents

Specialization in AI: Not “Do-Everything” AI

Now that we’ve laid the groundwork for understanding AI agents, let’s address a common misconception:
AI isn’t a magic “do-everything” machine.

Its real power lies in specialization—tailoring its capabilities to specific processes, workflows, and challenges. In supply chain management, this targeted focus can revolutionize operations by enhancing efficiency and adaptability.

Workflows vs. Agents: Understanding the Difference

Workflows:

Think of workflows as orchestrated systems. These are predefined code paths where Large Language Models (LLMs) and tools follow a set sequence of actions to complete tasks. Workflows are structured, efficient, and ideal for predictable, repeatable processes.

Examples:

• Automating purchase orders.
• Generating weekly inventory reports.
• Scheduling supplier follow-ups.

Agents:

Agents take it a step further. They’re dynamic systems where LLMs don’t just follow instructions—they direct their own processes and decide which tools to use and when.

Agents maintain control over how they accomplish tasks, adapting to changes in real time.

Examples:

• Identifying bottlenecks in your logistics chain and rerouting shipments.
• Negotiating supplier terms autonomously based on live market data.
• Adjusting inventory forecasts dynamically during seasonal spikes.

The Most Important Question: Is It Better, Faster, and More Affordable?

Sourcing Simplified: A 3-Step Exercise for Better Pricing and Supplier Selection

Getting a new list of materials to source can feel overwhelming.

The Traditional Way:

• Open Excel.
• Make countless notes.
• Send thousands of emails.
• Juggle phone calls like a makeshift CRM.

In the end, you often choose the same supplier because it’s easier—and, of course, you overpay for materials.

The AI-Driven Way:

Let AI agents handle the complexity, enabling you to:

1. Streamline sourcing workflows.
2. Automate supplier communications and comparisons.
3. Identify better pricing and supplier options, saving time and money.

Ready to simplify your workflows and optimize your operations? AI agents are here to help.