Agentic AI Strategy - Risks, Rewards, and Realities of Agentic AI

Last week, I sat in a boardroom where the CEO leaned back and asked: “So… if we let these agents run, what’s the worst that could happen?”

It wasn’t a flippant question. It was the right one.

Because while the promise of AI agents is exciting - speed, efficiency, customer responsiveness — the risks are equally real. And in my experience at Beyond: Putting Data to Work, the smartest leadership teams are those that balance both sides of the equation.

The Rewards

Let’s start with the upside, because it’s what gets most executives leaning forward.

• Speed and Scale: Agents can run workflows in seconds that humans take hours or days to complete.

• 24/7 Responsiveness: Unlike human teams, they don’t sleep — which means customer service, IT operations, and supply chains can run continuously.

• Cross-Enterprise Orchestration: They don’t stop at department boundaries. Agents can connect finance, operations, and marketing in ways that manual processes never could.

• Strategic Agility: Leaders tell me they’re excited about how agents could reduce “time to decision” — not just faster answers, but faster action.

The Risks

Of course, those same strengths create new dangers if left unmanaged.

• Loss of Control: Agents are autonomous. Without clear governance, they can act in ways the business didn’t intend.

• Poor Data = Poor Decisions: If the inputs are flawed, the outputs are worse — only faster. We’ve seen cases where agents amplify existing data problems rather than solve them.

• Regulatory and Reputational Exposure: In financial services, healthcare, and other regulated industries, a single unexplainable agent action can lead to compliance breaches or loss of trust.

• Workforce Resistance: Employees either don’t trust the agents, or lean on them too heavily. Both create cultural risks.

These risks aren’t reasons to avoid agents — but they are reasons to be deliberate.

The Realities

What strikes me most in conversations with C-suites is that the reality is rarely all reward or all risk. It’s a messy middle ground.

• Pilots Deliver Promise, Scaling Exposes Pain: In small proofs of concept, agents look miraculous. At scale, the challenges of data, integration, and governance quickly surface.

• Trust Takes Time: Executives often underestimate how much monitoring, guardrails, and transparency are needed before agents can be trusted to act autonomously.

• Not Every Process Needs an Agent: Some leaders fall into the trap of “agentise everything.” In reality, the best outcomes come from focusing on high-value, repetitive, cross-functional processes.

At Beyond, we call this the “reward-to-risk ratio” — making sure that where agents are deployed, the upside clearly outweighs the potential downside, and that governance mechanisms keep that balance in check.

What the C-Suite Should Do

Instead of asking “should we use agents?” the better questions are:

• Where are the biggest rewards if we succeed?

• Where are the biggest risks if things go wrong?

• What controls and operating model changes do we need to tip the balance in our favour?

Framed this way, the conversation becomes less about hype and more about strategic choice.

Final Thoughts on Agentic AI Risk

AI agents will reward the bold — but only if they are also disciplined.

At Beyond: Putting Data to Work, we’ve seen both sides: the excitement of agents delivering rapid wins, and the frustration when pilots stall due to poor data, unclear governance, or cultural resistance. The lesson is simple: you can’t separate the technology from the strategy, governance, and culture that surround it.

For executives, that’s the real work of building an Agentic AI Strategy — not just chasing the rewards, but managing the risks and navigating the realities.

Because the organisations that strike that balance will be the ones that thrive in the agent-driven future.