When you purchase through links on our articles, Future and its syndication partners may earn a commission.

Agentic AI (sometimes called multi-agent AI systems) is poised to revolutionize business operations. Joe Dunleavy, Global Vice President and Head of AI Pod at Endava, explains how this exciting technology will pave the way for more transparent, verifiable and sustainable use of AI and how its impact will transform businesses at scale.

Until now, humans had to be in the driver’s seat when it came to providing granular instructions to AI technology. This ensures that the AI ​​is not only pointed in the right direction in terms of results, but also helps minimize potential risks such as hallucinations, misinformation or bias. Additionally, organizations that deploy AI often simply improve the efficiency of specific tasks, reaping short-term value rather than targeting large-scale autonomous automation.

However, AI systems are now capable of handling more ambitious business processes, decision-making and data transformations. Agentic AI is poised to revolutionize how organizations across all industries can leverage this technology to their advantage. With the help of agentic AI, they will soon be able to automate processes in entirely new, more efficient and autonomous ways, enabling them to solve complex business problems at scale and faster. But how can we achieve this in the most efficient, secure and compliant way possible?

The three stages of AI transformation

To achieve this level of performance, automation and autonomy, AI requires a solid foundation. The transformation evolves in three phases. The first stage focuses on improving daily work by assisting with tasks such as summarizing documents or generating assets such as presentations, leading to faster, more cost-effective and more accurate results. In the next step, automation processes will be further integrated with business goals. At this point, AI takes on more responsibility in task sequences, working alongside people rather than simply following individual commands. In this way, AI evolves from a tool to a trusted partner.

In the third stage, the technology achieves an even higher degree of autonomy. At this point, AI is no longer “just” a teammate that collects, summarizes, and analyzes information. Instead, it takes on a more “proactive” advisory role. This is enabled by AI-based autonomously acting agents (agentic AI), which can operate without direct human intervention in any environment, including different large language models (LLMs) and platforms cloud. Unlike traditional AI models, programmed specifically for single processes, agentic AI approaches can handle much more complex tasks.

In a team of autonomous agents (multi-agent system), each agent is assigned an individual role and receives the necessary knowledge. These agents can communicate and interact with each other and their environment, react to changes and contextualize their tasks to make holistic decisions and achieve the best possible outcome. This all works with minimal human oversight, without the need to manually provide input every step of the way.

Although agentic AI technology is still in its infancy, these systems can safely advance workflows with minimal supervision. As autonomous agents automatically perform time-consuming, mundane, and repetitive tasks, they can accelerate the amount of work completed in a specific time frame, which can be applied across the enterprise to drive efficiencies at scale . This frees up employees who can in turn focus on more complex strategic and creative challenges. This approach nurtures the potential of each employee, increases employee job satisfaction, and drives business growth and value.

Benefit from autonomous agents – but not without transparency

Autonomous agents can be used to manage complex and nuanced workflows in every industry imaginable. However, AI systems are typically built as black boxes whose functions and processes are neither visible nor understandable to their users. As a result, tightly regulated industries such as healthcare, financial services, insurance and energy – where strict rules govern the collection, processing and storage of sensitive data – are often reluctant to implement this technology in their daily business operations. After all, they must comply with specific requirements when collecting, processing, using and storing (sensitive) data. Just as it is important not only to find the right answer but also to demonstrate the steps taken in fields like law or accounting, these sectors must be able to clearly show how AI arrives at its results to meet the compliance requirements.

The solution to this challenge is a data-driven approach. For these industries to use AI in their favor and optimize their processes, they must be able to open the black box and disclose its contents in a transparent and verifiable manner. An autonomous multi-agent system that reveals how AI agents ingest and transform data is ideal for addressing this challenge, because each time an agent acts on the data, the system captures relevant information surrounding the operation, creating thus a clear line of sight and understanding of the operation. decision that the agent makes as part of an audit trial. This distribution both makes data and processes visible and understandable, and effectively circumvents common AI problems, such as AI hallucinations.

With the help of agentic AI, businesses can automate sophisticated processes and solve complex business problems at scale, all while remaining compliant. As a result, technology is essential to unlocking productivity, satisfaction, business growth and maintaining a competitive advantage. This does not mean that employees will be replaced by technology. Although this requires less human intervention and monitoring, users remain in control of the AI ​​system and remain at the heart of operations. AI may be in charge, but users dictate the direction and can hit the brakes at any time.

We have presented the best cloud storage.

This article was produced as part of TechRadarPro’s Expert Insights channel, where we feature the best and brightest minds in today’s technology industry. The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you would like to contribute, find out more here: https://www.techradar.com/news/submit-your-story-to-techradar-pro