Today, we’re thrilled to sit down with Dominic Jainy, a seasoned IT professional whose deep expertise in artificial intelligence, machine learning, and blockchain has positioned him as a thought leader in transformative business technologies. With a passion for applying cutting-edge solutions across industries, Dominic offers unique insights into how agentic AI is revolutionizing tax and compliance processes, particularly for users of Microsoft Dynamics. In this conversation, we’ll explore the meaning and impact of agentic AI, its practical applications in compliance automation, and how it’s enhancing ERP systems. We’ll also dive into the challenges of balancing automation with trust and what the future holds for this rapidly evolving field.
How would you define “agentic” in the context of AI, and what makes it a game-changer for tax and compliance?
Agentic AI refers to software agents that don’t just assist with information or answer questions but actually take action on behalf of users, executing tasks autonomously while still under human oversight. In tax and compliance, this is a game-changer because it shifts the burden of repetitive, rules-based work—like calculating taxes or preparing filings—away from people. Unlike traditional tools that require constant input, these agents can handle workflows end-to-end, adapting to complex scenarios. It’s like having a virtual team member who knows the ins and outs of global tax laws and can act on them without needing to be micromanaged.
What do you think is driving the push toward agentic AI in compliance right now?
It’s really a perfect storm of factors. First, AI technology has matured significantly, with innovations like model context protocol servers enabling seamless interactions between systems and agents. Then there’s the growing complexity of global tax regulations—businesses are dealing with more rules and jurisdictions than ever. On top of that, customers are demanding solutions that save time and reduce errors. So, the tech is ready, the need is urgent, and the environment is ripe for AI to step in and tackle these challenges head-on.
Can you walk us through how agentic AI practically functions in a compliance setting?
Absolutely. These AI agents can take on a wide range of tasks, from automating tax calculations based on location and product type to managing workflows for filings or even securing necessary registrations. They interact with users through natural language, so you don’t need to code complex integrations—you can just tell the agent what you need, and it parses the request, pulls data from APIs, and delivers results. They also connect with other systems or agents to streamline processes, making sure everything from data input to final output is handled efficiently.
How do technologies like model context protocol servers support this kind of AI-driven automation?
Model context protocol servers, or MCP servers, are essentially the backbone that allows AI agents to communicate with platforms and other systems. They register APIs and enable agents to interpret natural language inputs, extract relevant data, and execute tasks without manual coding. For example, if you’re calculating tax on a sale, an agent can take your spoken or typed request, process it through the MCP server, interact with the tax platform, and return the result in plain English. It removes technical barriers and makes automation accessible and intuitive for users.
What steps are crucial to ensure trust and accuracy when AI handles sensitive tax data?
Trust is paramount, especially with something as critical as tax data. The key is building robust security protocols and governance policies into the AI systems—think strict access controls and encryption to protect sensitive information. Equally important is keeping humans in the loop at key decision points, whether it’s approving a tax classification or reviewing a prepared return before submission. This hybrid approach ensures the AI handles the heavy lifting while humans provide oversight, maintaining accuracy and accountability to meet regulatory standards.
In what ways does agentic AI enhance the experience for Microsoft Dynamics users specifically?
For Microsoft Dynamics users, agentic AI builds on the platform’s existing tax capabilities by addressing more complex, global compliance needs. It acts as a specialized partner, stepping in when requirements go beyond standard calculations—think multi-jurisdictional tax rules or intricate filings. These agents can observe, advise, and execute tasks directly within the Dynamics ecosystem, reducing manual effort and helping businesses stay compliant without getting bogged down by the nuances of international regulations.
Could you share a real-world scenario where agentic AI has made a difference for a Dynamics user?
Sure, let’s consider a Dynamics customer onboarding a tax compliance solution. An AI agent, accessible through a browser extension, can guide them step-by-step—highlighting required fields, auto-filling data, and ensuring the setup aligns with their specific needs. Once live, the agent sticks around to answer questions or troubleshoot in real time. Another example is an agent working within Microsoft Outlook, catching invoices as they come in, checking for compliance issues like missing taxes or exemption forms, and then seamlessly feeding clean data into Dynamics. These are tangible ways AI saves time and prevents errors before they escalate.
How do you see tax and compliance fitting into the larger story of AI transforming business systems?
Tax and compliance is a prime candidate for AI transformation because it’s so data-heavy and rules-driven—areas where automation shines. It frees up businesses from mundane, low-value tasks, letting them focus on strategic priorities. Plus, as AI processes all this data, it uncovers insights that can inform better decision-making. So, it’s not just about efficiency; it’s about turning a traditional cost center into a source of competitive advantage by automating the routine and elevating the strategic.
What’s your forecast for the future of agentic AI in compliance over the next few years?
I believe we’re just at the beginning. Over the next few years, we’ll see agentic AI become even more collaborative, with agents not only interacting with humans but also with each other across platforms to solve complex problems. Imagine agents from different systems negotiating tasks like preparing returns or resolving discrepancies without human intervention. As ERP systems and partner technologies evolve, this agent-to-agent communication will drive unprecedented levels of automation and efficiency in compliance, fundamentally changing how businesses operate.