By: Sarah Legendre Bilodeau, Senior Vice President, Artificial Intelligence Consulting Group – Videns, powered by COFOMO

A new lever is emerging at the heart of business innovation strategies: agentic AI. While the concept may sound abstract to some, its potential for organizations is immense. At a recent conference on “AI for Business” presented by Les Affaires, I had the opportunity to explain why this technology is generating so much excitement and just as many questions.

What exactly is agentic AI?

Unlike traditional AI models that perform a single, isolated task, agentic AI acts as a system of specialized “agents” that work together to manage an entire process from start to finish.

Imagine, for instance, a claims process in the insurance sector: a customer contacts the company, an AI agent responds in natural language, collects the required information, verifies the claim’s validity across multiple systems, applies internal policies, and returns a final decision to the customer.

Agentic AI is the orchestration of multiple technologies working in concert, powered by artificial intelligence. It’s a system capable of understanding, analyzing, deciding, and acting, with minimal or no human intervention.

Why does it matter for businesses?

Two priorities dominate nearly every organization today: optimizing operational efficiency and enhancing the customer experience. Agentic AI addresses both.

1. Greater productivity

Manual processes are slow, costly, and require scarce human resources.

Agentic AI helps to:

• Handle more requests in less time
• Reduce processing delays
• Standardize decision-making
• Automate repetitive tasks

2. Enhanced customer experience

Customers expect quick, consistent answers 24/7. Agentic AI makes that possible, often faster than traditional workflows.

3. Always-on availability

AI agents don’t have working hours or human limitations.”

AI agents never take breaks. They deliver continuous service, especially valuable in high-volume customer or operational environments.

Implementation challenges: between technological complexity and organizational maturity.

The promise is great but the road to get there is just as demanding. Before reaping the benefits, organizations must navigate technological constraints, legacy systems, and cultural transformation. This journey requires vision, discipline, and adaptability.

1. Most companies aren’t “digital natives”.

Across industries from manufacturing to education and even in tech, systems are often heterogeneous, outdated, and poorly integrated. Data is scattered, poorly governed, or difficult to access. Yet, data is the foundation of any agentic AI system.

Data is the foundation of any agentic AI system.”

2. Regulated environments add additional complexity.

Banking, insurance, and healthcare are highly regulated sectors where compliance requirements can slow innovation. Agentic AI must operate within strict, transparent, and well-documented frameworks.

3. The cultural barrier: our relationship with error.

This is often the most underestimated challenge. We easily forgive human errors but we’re much less forgiving of errors made by technology.

Yet, every AI system, agentic or not, carries a margin of error. Each component introduces potential risk. Learning to manage, monitor, and continuously improve that risk requires a significant cultural shift.

Where to begin?

The goal should never be “to do agentic AI.” The goal is to improve a process and create true value. Achieving that requires a structured, thoughtful approach where each step builds on the last.

Test, learn, and then add the next building block.”

Here’s how to start your organization’s agentic AI journey:

1. Look beyond the buzzword.

Technology is an enabler. Start by understanding your needs, your current processes, and your business context. Only then should you assess how AI can drive improvement.

2. Master your internal processes.

An inefficient process doesn’t become better with AI. It actually becomes more inefficient faster and at scale. Without optimal internal processes, agentic AI can create more problems than it will solve.

3. Scale ambition gradually.

Don’t try to automate an entire process at once. Identify instead:

• One step in the workflow
• A specific decision block
• A small automation opportunity
• Possibly with initial human supervision

Test, learn, and then add the next building block. This is how robust agentic systems are built.

4. Don’t start with a customer interface.

Many think of AI agents that interact directly with customers but that’s rarely the best starting point. Begin internally, with employees or advisors “augmented” by AI. Make mistakes, validate rules, and stabilize the system behind the scenes before deploying it externally. The quick wins are often found in internal systems and processes.

Conclusion: advancing with pragmatism and ambition.

Agentic AI represents a tremendous opportunity for companies seeking to modernize operations, improve efficiency, and deliver superior customer experiences.

But success requires:

• A clear understanding of internal processes
• A realistic roadmap
• Thoughtful risk management
• Gradual evolution
• And a cultural shift in how we approach errors

Adopting agentic AI means building organizations that are more agile, intelligent, and human-centric. It’s about turning experimentation into impact, and vision into measurable results. And organizations that embrace this with pragmatism and ambition will secure a lasting competitive edge.

Ready to explore the potential of agentic AI for your organization?

Contact our AI experts and discover how COFOMO can guide your transformation.