Booster Analytics

In the rapidly evolving world of artificial intelligence, Agentic AI is the next frontier, promising autonomy, adaptability, and intelligence that goes beyond mere automation.

Let’s not sugarcoat it: the hype often outpaces understanding.

As a CTO and senior advisor in Thailand, I’ve often seen managers either dive in headfirst without a clear plan or hesitate to act, fearing they’ll sink resources into yet another tech experiment gone wrong. Neither approach will position your organization to leverage the transformative power of Agentic AI effectively.

I will give a straightforward, no-nonsense guide to get you started with Agentic AI, ensuring that you’re making informed, strategic decisions.

1. Understand What Agentic AI Is (and Isn’t)

Agentic AI refers to AI systems capable of autonomous decision-making, learning from context, and acting on behalf of users with minimal oversight. These aren’t your typical rule-based systems or ML models spitting out static predictions — they’re adaptive and goal-driven.

What it’s not: It’s not magic, nor is it a substitute for strategic direction. Managers often misunderstand autonomy as a hands-off solution. Agentic AI still requires human oversight, ethical guardrails, and clear objectives. It will not turn you into a great manager.

Pro Tip: Before jumping in, ensure your team has a foundational understanding of Agentic AI. Hold workshops or briefings to align everyone on terminology, use cases, and limitations.

2. Start Small, but Think Big

The biggest mistake is overcommitting to an AI initiative without clear proof of concept. Rushing head-down into agentic AI will not make it a successful initiative. Begin with a small, targeted pilot project where the potential ROI is tangible. This could be in customer service (e.g., autonomous virtual assistants), supply chain optimization, or personalized recommendations.

I am a big advocate of starting small but thinking long-term. Agentic AI should fit into your broader digital transformation roadmap, not sit as a siloed experiment.

Actionable Step: Identify one or two areas in your organization where decision-making is repetitive but context-sensitive. These are ripe for initial Agentic AI applications.

3. Invest in Data Readiness

Agentic AI thrives on context-rich, high-quality data. If your organization’s data is a mess — scattered, inconsistent, or incomplete — your AI agent will be about as useful as a blindfolded navigator.

Checklist for Data Readiness:

• Do you have a centralized data repository?

• Are your data pipelines clean and reliable?

• Do you have a governance framework in place to ensure privacy, security, and compliance?

I have seen several companies asking me to help implement and deploy Agentics AI without one single ready pipeline. Without these foundations, deploying Agentic AI will lead to frustration and underperformance.

4. Build Cross-Functional Teams

Agentic AI isn’t just an IT project. I witnessed several companies that treated this as another IT project. Its success hinges on collaboration between tech, business, and domain experts. You’ll need a team that includes:

• AI/ML specialists will design and train the system.

• Business analysts to align AI objectives with organizational goals.

• Domain experts to provide the contextual knowledge the AI needs to function effectively.

Leadership Tip: Appoint a clear project owner — someone who can bridge technical expertise with strategic vision.

5. Focus on Explainability and Ethics

An agentic AI that acts autonomously without transparency is a recipe for disaster. Managers need to ensure that every decision made by the AI can be explained, justified, and audited.

Why It Matters:

• Regulators are paying close attention to AI. Compliance is non-negotiable.

• Without explainability, employees and stakeholders won’t trust the system.

Ethical considerations are equally important but often ignored. Define clear boundaries for what your AI can and cannot do. For instance, avoid using autonomous systems in contexts where decisions involve sensitive moral or legal implications.

6. Iterate and Learn

Agentic AI systems improve over time through feedback. However, they need mechanisms to capture, evaluate, and incorporate feedback effectively. This mechanism is where many managers drop the ball — deploying and forgetting.

Best Practice: I asked my team and companies to set up a monitoring system to track performance metrics and user feedback. I also asked for regular review and refinement of the AI’s parameters and objectives.

7. Communicate Value Early and Often

Introducing Agentic AI can create fear and resistance within your organization. Employees may worry about job displacement, while stakeholders may question the ROI. Proactive communication is your ally here.

• For Employees: Emphasize that AI is a tool to augment their roles, not replace them.

• For Stakeholders: Showcase early wins and clearly articulate long-term benefits.

CTO’s Insight: A transparent, incremental approach builds trust and minimizes pushback.

8. Prioritize Security and Scalability

Do not forget that Agentic AI systems often interact with sensitive data and critical processes. Security must be baked into your AI architecture from day one. Additionally, plan for scalability. What works for a pilot might buckle under the demands of full-scale deployment.

9. Know When to Walk Away

Not every process or problem is a good fit for Agentic AI. Avoid the trap of forcing AI into situations where simpler, rule-based systems suffice. If the ROI isn’t there, be prepared to pivot or put the project on ice.

Final Thoughts

I believe that Agentic AI has the potential to revolutionize business operations, but only if implemented thoughtfully and strategically. As a manager, your role is to bridge the gap between ambition and execution. By starting small, prioritizing data readiness, and fostering collaboration, you can set the stage for transformative outcomes.

Remember, Agentic AI isn’t just about adopting new technology; it’s about rethinking how your organization makes decisions. Done right, it can be the competitive advantage you’ve been waiting for.