AI Agent Best Practices: How to Avoid Early Pitfalls

This is both an extraordinary opportunity and a genuine leadership test. Adopt agentic AI well and you unlock efficiency and innovation at a scale traditional automation has never delivered. Adopt it poorly and you create brittle systems, governance blind spots, and an AI strategy stuck in pilot purgatory. Let’s take a closer look.

The upside is enormous.

Handled deliberately, agentic AI allows IT leaders to:

• Strip away operational friction that has slowed organisations for years
• Free teams to focus on customer experience, product design, and innovation
• Modernise legacy portfolios without multi-year rewrites
• Build a more adaptive organisation where people and AI collaborate effectively.

This is the promise that excites CIOs and CTOs: the chance to accelerate transformation without tearing down what already works.

And the risks are real.

Move too quickly or without structure, and you could just as easily:

• Accumulate ungoverned, brittle automations
• Confuse experimentation with impact
• Create a tangle of agents, scripts, and one-off tools no one fully owns
• Watch your AI roadmap devolve into disconnected pilots.

These are the traps that keep most agentic AI deployments stuck in early-stage experimentation. But they’re avoidable with the right starting principles.

Preparing your organisation for agentic AI

Here’s a basic framework to help your business leverage AI to deploy systems that truly change the business.

1. Start where friction is highest, not where hype is loudest

The best early wins aren’t glamorous; they’re operational. 

Look for processes that deal in complexity and repetition: document intake, approvals, onboarding, compliance checks, case handling, or multi-system coordination. These often have clear, measurable outcomes (reduced backlog, faster cycle time, lower error rate), making them perfect candidates for agentic automation.

Instead of chasing buzzworthy use cases, target the work that employees quietly struggle through every day. That’s where agentic AI will show its value fastest.

2. Treat “agent governance” the way you once treated API governance

The strategic question for every IT leader is becoming: If every system in your enterprise could act on its own, what would you trust it to do?

Agent sprawl is the new shadow IT. To prevent it, you’ll need:

• Standard ways to define agent permissions and boundaries
• Central monitoring of actions, errors, and human handoffs
• Clear ownership: who investigates when an agent behaves unpredictably?

Build this discipline early, and you avoid a future where dozens of agents are making decisions no one is tracking.

3. Pick platforms that can evolve alongside your architecture

Avoid the temptation to lock into a single AI vendor. What you want instead is architectural flexibility:

• Use platforms that let you bring your own models – or mix different AI providers
• Ensure strong integration with your existing systems (SAP, Salesforce, core banking, HRIS)
• Choose tools that embed agents directly into workflows rather than bolting them on

This is where platforms like OutSystems are positioning themselves: as the layer where leaders can design, build, and orchestrate agents consistently across the entire estate. The right platform shouldn’t constrain your AI strategy; it should make your estate more adaptable as AI capabilities evolve.

4. Don’t underestimate the human shift

Agentic AI won’t just change your systems. It will change your people.

• Developers will shift from building everything manually to supervising, steering, and validating AI-generated logic.
• Business users will expect faster, iterative delivery and more self-service.
• Governance teams will need frameworks designed for systems that act, not just systems that store or calculate.

The CIOs who treat agentic AI as a team sport, not an automation takeover, will navigate the transition far more successfully. This is as much an organisational shift as it is a technical one.

The technology is arriving either way

Agentic AI isn’t waiting for you to be ready. It’s already seeping into SaaS products, developer tools, enterprise platforms, and even your shadow IT.

The advantage will belong to leaders who prepare deliberately and who start with the correct problems, put governance in place early, choose adaptable platforms, and guide their teams through the changing nature of work.

The next wave of AI won’t be won by the organisations with the most agents. It will be won by those with the most intentional ones. And that begins now.