Making agentic automation more reliable and robust

Imagine a world where artificial intelligence (AI) doesn’t just complete tasks on demand, but also determines which tasks need to be prioritized and how best to accomplish them. This is the promise of agentic automation: AI that adapts autonomously in real-time to complex challenges. Once a buzzword, agentic AI is now gaining traction as a sophisticated tool for businesses, with heavy investments from major companies like Google and Microsoft. Forrester recently named agentic AI a top emerging technology and Gartner anointed it the top tech trend for 2025.

However, such vast potential brings with it significant uncertainty. For one, the rapid growth of generative AI has introduced challenges around data compliance, AI ethics and even basic errors like hallucinations – where AI confidently answers questions with fabricated information.

As businesses explore the potential of agentic automation, critical questions arise. While it offers flexibility and autonomous decision-making, is it the right fit for all types of processes? For tasks requiring high predictability, minimal flexibility and zero tolerance for errors, more deterministic automation may be better suited. For tasks where agentic automation is essential, how can we ensure its decisions are consistently reliable, secure and compliant, despite AI’s capacity for inaccuracy and bold extrapolation?

Automation or accuracy: Do we need to choose?

Unlike traditional automation, which sticks to fixed, predictable rules, agentic automation empowers AI to make real-time, data-driven decisions based on complex inputs. It solves problems, makes judgments and adapts on the fly without constant human intervention. This opens up the opportunity to automate complex business processes that require some level of flexibility and creativity from start to finish, boosting efficiency, cutting down on errors and freeing up employees to focus on higher-value tasks that drive real business growth.

Yet as AI begins making more decisions on its own, business leaders need to ensure these systems are reliable and accurate. After all, even small errors could create big risks if AI doesn’t fully understand complex situations.

The risk-averse may be inclined to shy away from agentic AI altogether, but avoiding it is no longer an option for forward-thinking businesses. According to Deloitte, 25 percent of companies using generative AI today plan to launch agentic AI pilots by 2025, with that number expected to rise to 50 percent by 2027. What’s more, a GlobalData report predicts that, by 2028, 15 percent of daily business decisions will be made autonomously. Ignore this shift, and you risk falling behind.

Clearly, businesses need agentic AI for the processes that require agentic capabilities, but they also need that solution to be trustworthy. The good news is that a crucial step in building that trust lies not in developing new technologies, but in integrating proven, foundational tools we already have, such as intelligent document processing (IDP).

How IDP supports agentic automation

IDP might not be the first technology you think of when it comes to agentic AI, but it’s the solution that can make AI-driven decisions more accurate and trustworthy. By automatically extracting, classifying and interpreting data from documents via purpose-built AI technologies, IDP acts as a precision filter for unstructured data and turns messy, raw information into clean, actionable insights.

This transformation is crucial for agentic AI, which can create errors and make unreliable decisions when hindered by poor-quality data. IDP processes complex, real-world data – whether it’s invoices, contracts or emails – with remarkable speed and precision, providing AI systems with accurate, structured and compliant information. This eliminates the guesswork and risks associated with inaccurate data and allows agentic AI to make smarter choices.

Put simply, IDP empowers agentic AI to perform at its highest capacity. Take accounts payable automation, for example. With the power of IDP and agentic automation, the entire invoice processing workflow becomes faster and more efficient. First, IDP automatically scans and extracts crucial data from incoming invoices – everything from vendor details to payment terms. Then, agentic AI takes over. Using predefined rules, it validates the invoice data, cross-checks it with purchase orders and flags any discrepancies. Once everything is verified, the AI can approve payments on its own, making the process faster and more efficient.

For any complex cases or exceptions, finance teams can still step in, ensuring accuracy and maintaining control. This integration between IDP and agentic automation not only accelerates the payment cycle but also reduces errors and frees up valuable time for finance teams to focus on more advanced tasks.

Accuracy in agentic AI

As with any groundbreaking technology, there are still many uncertainties surrounding agentic automation. Experts caution businesses to proceed thoughtfully, weighing risks like oversight, accountability and governance. Beyond the challenges lies an exciting future, one where businesses operate smarter, faster and more efficiently.

Generative AI and agentic automation have the potential to transform businesses, and IDP helps provide a solid foundation for efficient, scalable and trustworthy automation. By acting now and adopting the right tools and strategies, companies can seize the opportunity to transform their operations and lead the charge in the AI-powered world of tomorrow.