Agentic AI: Human Judgment, Empathy, and Intuition are Non-Negotiable
Blossom Furtado, the Marketing Director for EMEA at Cisco, says when it comes to brand, ethics, messaging, or anything with human nuance—humans need to stay in the loop
How do you define Agentic AI, and how does it fundamentally differ from traditional chatbots or rule-based automation?
From a marketing professional’s lens, Agentic AI is a bit of a game-changer. Unlike traditional chatbots that wait for you to spoon-feed them a command and then follow a fixed script, agentic AI actually thinks. It doesn’t just respond—it acts. It has intent, memory, reasoning, and the ability to carry out tasks independently across multiple steps. Like a mini-marketer on autopilot (minus the espresso addiction).
Where a chatbot might help a user find a whitepaper, an agentic AI could notice a customer segment’s behavior shifting, create a campaign plan, launch an A/B test, and optimize in real-time—without constant nudges. It’s the difference between a vending machine and a personal shopper who knows your size, mood, and calendar—and already ordered your outfit before you realized you needed it.
For us in marketing, it’s a leap from automation to autonomy. This means smarter personalization, faster execution, and freeing up human minds for actual strategy, storytelling, and creative problem-solving. Basically, it’s not about replacing marketers—it’s about unburdening them so we can focus on the things only humans can do well: connect, imagine, empathize, lead.
Beyond task automation, what complex, multi-step problems are agentic AIs uniquely positioned to solve that current AI models cannot?
The real power of agentic AI kicks in when you’re looking at complex, multi-layered problems that go way beyond simple task automation. We’re talking about challenges that require context, judgment, adaptability, and continuous iteration—things current AI models or rule-based systems just can’t handle without constant human babysitting. So really, agentic AI moves us from task doers to outcome drivers. It’s not “give me X,” it’s “here’s my goal—figure it out.”
How much autonomy should Agentic AI have in decision-making, and where should humans remain in the loop?
Agentic AI should have autonomy—but not a blank cheque. Let it run with repetitive, data-heavy, decision-light tasks (from a marketeers lens I’m thinking campaign tweaks, A/B testing, budget shifts). That’s where it thrives and frees us up.
But when it comes to brand, ethics, messaging, or anything with human nuance—humans need to stay in the loop. Not because AI can’t do it, but because it shouldn’t do it alone. Our judgment, empathy, and intuition are non-negotiable.
What’s the next frontier for Agentic AI—will we see AI “agents” collaborating like human teams?
The next frontier? AI agents collaborating like teams—each with a specialty, sharing context, dividing tasks, and working toward a common goal. Think of it as your own little marketing squad: one agent crunching audience data, another crafting content, another optimizing media spend—all talking to each other, learning together, and reporting back with results. It’s not science fiction anymore. It’s where we’re headed—and fast.
