What Are AI Agents (and Why They Matter for Business?)
- Beyond Team
- 4 days ago
- 4 min read
If 2023 was the year of chatbots and 2024 was the year of copilots, then 2025 is quickly shaping up to be the year of AI agents.
At Beyond: Putting Data to Work, I’m hearing the same questions come up again and again from senior leaders:
“Is this just another hype cycle?”
“What exactly is an AI agent?”
“How should we even start thinking about this in the boardroom?”
These are good questions — and ones worth answering clearly.
What Are AI Agents?
At their core, AI agents are autonomous software entities that can perceive, reason, and act to achieve goals — often with minimal human input.
That’s a big shift from traditional AI, which has always been about prediction, pattern recognition, or (more recently) generating content. AI agents are different because they:
Understand context by pulling in data from multiple systems.
Make decisions about what needs to happen next.
Take action — from sending an email, to updating a CRM, to rebalancing stock in a warehouse.
Learn as they go, adapting based on outcomes.
In short: they don’t just assist, they act.
When I explain this to executives, I often use a simple analogy: if a GenAI model is like a talented intern who drafts ideas for you, an AI agent is like a trusted junior manager who doesn’t just draft, but takes ownership of delivering the outcome.
How AI Agents Differ from Generative AI
This distinction matters because a lot of leaders still use “GenAI” and “AI agents” interchangeably.
Generative AI is about creation: text, images, code, forecasts.
AI agents are about orchestration: taking those creations, deciding what to do next, and executing until the task is complete.
Example I often give in workshops:
A GenAI model might draft a customer service email.
An AI agent could draft it, send it, log the interaction in CRM, open a support ticket if needed, and schedule a follow-up — without you lifting a finger.
That leap from “content generation” to “goal-directed action” is why this technology is on every board agenda I’ve been part of lately.
Why the C-Suite Is Paying Attention
From my conversations, here are the three themes I hear most often from executives when it comes to AI agents:
1. Productivity vs. Transformation
Some leaders want to use agents for straightforward efficiency plays — automating tasks that chew up time. Others are asking how agents might actually change their operating model. The truth is, both are possible. The bigger prize is transformation, but it needs foundations first.
2. Breaking Down Silos
I can’t count the number of times we’ve worked with clients where marketing, operations, and finance all run on different systems, with no joined-up view. AI agents — if designed properly — can orchestrate across silos. That’s powerful, but it also raises questions about ownership, governance, and control.
3. Risk Appetite
The number-one hesitation I hear? “How do we make sure these agents don’t go rogue?” It’s not paranoia — it’s a sensible governance question. At Beyond, we help boards think about their risk ambition — where they’re comfortable letting agents act autonomously, and where human oversight must remain.
Real-Life Scenarios We’re Seeing
Without naming names, here are some examples of the conversations we’re having:
A retail leader asking if agents could run dynamic pricing adjustments across stores without human sign-off.
A CFO wondering whether agents could reconcile thousands of invoices overnight instead of tying up teams for weeks.
A marketing executive frustrated that campaign execution still takes weeks — asking if agents could plan, generate, and launch content in days.
These aren’t “science fiction” use cases. They’re real, near-term questions being asked in boardrooms right now.
Challenges Leaders Must Confront
Of course, none of this is plug-and-play. When we sit down with clients, the conversation often circles back to the same challenges:
Data quality – You can’t have agents making decisions on bad data. Garbage in, garbage out.
Governance – Who’s accountable if an autonomous system makes the wrong call?
Change management – Employees need to see agents as enablers, not threats.
Integration – Most enterprises still wrestle with legacy systems. Connecting them seamlessly to agents isn’t trivial.
These are exactly the kinds of conversations we specialise in at Beyond: ensuring organisations are agent-ready — not just technically, but strategically and culturally.
Where to Begin
My advice to leaders is simple:
Start small, prove value. Don’t launch a dozen agents at once. Pick one process where the business value is clear and the risk is low.
Build guardrails. Define where agents can act freely and where human sign-off is needed.
Measure outcomes. Not just cost savings, but customer experience, speed to market, and resilience.
Plan for scale. Think beyond pilots. If an agent works, how will you scale it across functions?
Final Thoughts
AI agents are more than just another AI buzzword. They represent a step-change: from machines that assist to machines that act.
At Beyond: Putting Data to Work, we’re seeing first-hand how quickly this conversation is moving up the agenda. The leaders who start exploring agents now — carefully, responsibly, with an eye on business outcomes — will be the ones best placed to shape the autonomous enterprises of tomorrow.
For me, the most exciting part isn’t the technology itself. It’s the questions executives are asking: What could this mean for how we work? How we serve customers? How we create value?
That curiosity — coupled with pragmatism — is the best place to begin. If you'd like to speak about this for your business feel free to reach out.
