What is Agentic AI?

AI is evolving fast. If we use Google Search (as it was in 2022) as a starting point, here’s the story so far: 

1. Google Search – You ask. It shows results.
2. ChatGPT (Generative or GenAI) – You ask. It writes or explains.
3. Custom GPT – You train a GPT. It answers in your context.
4. AI Assistant (Task-Oriented) – You define a goal. It helps manage the task.
5. Agentic AI (Goal-Oriented) – You set the goal. It initiates, executes, and updates you.

Agentic AI might be no more than the next step on the ladder, but it differs from the others in one key aspect — it doesn’t just respond, it acts. For example: 

You say:

“We have a tax audit scheduled next month. Can you help us get ready?”

🔄Traditional AI (Responds):

• Recommends documentation to gather
• Provides links to tax audit checklists
• Answers questions like “What is a digital audit trail?”

Useful, but you still do all the work.

🤖Agentic AI (Acts):

Once it knows your goal, it could:

1. Pull data from ERP, tax engines, and prior filings to create an audit prep file
2. Scan for anomalies in transaction-level VAT data using rules or prior flags
3. Compare reported tax positions with actual system entries to ensure alignment
4. Draft summary narratives explaining key numbers and adjustments
5. Send reminders to relevant team members for outstanding reconciliations
6. Generate a checklist tailored to your jurisdiction and audit scope.

In other words, it orchestrates multiple steps, draws from multiple systems, and proactively prepares you — not just answers questions. 

🎯 Why It Matters for Tax

This is more than conventional automation. In a tax transformation (TX) context, agentic AI bridges the gap between system potential and operational reality. It represents a leap from reactive reporting to strategic automation — the same kind that tax authorities seek through digitalization.

But here’s the catch: agentic AI is only as smart as the data and direction it’s given. As with all technology, agentic AI is no silver bullet and *not* about replacing people — it’s about enhancing what skilled professionals can achieve when freed from routine friction.

To function correctly, agentic AI needs structured information models, clear governance, and systems that are built to interoperate—not just tools that “talk.” The challenge ahead for tax professionals will be to supervise this and establish themselves within an upgraded ecosystem.

📩 So, What Next?

Most professionals now use GenAI—such as ChatGPT or Microsoft Copilot (step 2 on the ladder)—to boost personal productivity. But few have meaningfully progressed beyond that.

Before doing so—especially before building anything like your own agentic AI agent—you need a clear vision of what’s possible. That vision starts with understanding the process. Try asking your favourite GPT this:

“What would it take to evolve from asking you questions to building an AI agent that can act on my behalf in a tax context? Please include steps for setting goals, connecting to systems, and automating workflows.”

Let it show you what’s possible—then decide what you want it to do.

⚠️ But be warned: it’s not as simple as it sounds. Roughly 30% of agentic AI projects fail outright, and many more cause unintended consequences, miss expectations, or undershoot ROI. TX-style transformation remains critical.

Until next time …