How can your business harness agentic AI?

The relentless pace of artificial intelligence development presents both immense opportunity and significant confusion for IT leaders. Beyond the headlines surrounding large language models (LLMs), a more pragmatic evolution is taking shape: agentic AI. This isn't just another buzzword; it represents a fundamental shift from task-based automation to goal-oriented autonomous systems capable of tackling complex business processes. For organizations looking to drive genuine productivity gains and competitive advantage, understanding and strategically adopting agentic automation, exemplified by UiPath Agentic Automation approaches, is becoming critical.

The challenge lies in moving beyond simple automation or generic AI tools, often requiring significant human intervention and integration effort. Businesses need solutions that are deterministic, that work autonomously as they learn and interact across systems to achieve specific outcomes – the very definition of agentic behaviour.

Defining the 'agent': What makes agentic automation different?

Traditional Robotic Process Automation (RPA) has delivered significant value by automating repetitive, rules-based tasks and is a core component of agentic automation. General AI tools, including powerful LLMs, offer impressive natural language capabilities such as understanding and generation. However, they typically function as co-pilots or require specific prompts and integration to perform business tasks effectively.

Agentic automation represents the next logical step. An AI 'agent' is designed with a specific goal in mind. It can perceive its environment (digital or physical), reason about the steps needed to achieve its objective, make decisions, execute actions across various applications and data sources, and learn from the outcomes. Think of a skilled digital project manager, capable of navigating complexity and adapting to unforeseen circumstances. This capability moves automation from simply doing tasks to achieving outcomes. Importantly, agents are not here to replace robots or humans, but to work alongside them, co-existing with people to drive better decisions, faster execution, and more agile operations. The future is not humans vs. machines, but humans, robots, and agents working in harmony to deliver smarter, more adaptive, and outcome-focused workflows.

Beyond the hype: Why specialised agentic AI trumps generic tools for process automation

While general-purpose AI models are versatile, applying them effectively to intricate, multi-step business processes can be complex and resource-intensive. Agentic automation platforms, like those from UiPath, are purpose-built for this environment. 

They provide the necessary scaffolding – the ability to break down complex goals into manageable tasks, interact reliably with enterprise applications (often via robust APIs or UI automation), manage long-running processes, handle exceptions gracefully, maintain the ‘human-in-the-loop’ supervision, and apply essential corporate governance to AI agents.

Generic tools might struggle with the inherent fragility of interacting with diverse legacy systems or lack the built-in governance needed for enterprise deployment. Specialised agentic automation focuses on reliably executing end-to-end processes, integrating the power of AI models within a framework designed for enterprise-grade automation.

The productivity imperative: Unlocking savings and growth

The potential productivity gains from agentic automation are substantial. By autonomously overseeing complex workflows that previously required significant human oversight or were simply too complex for traditional automation, businesses can achieve:

1. Significant cost savings: Reducing manual effort in complex customer service inquiries, intricate data reconciliation, supply chain optimisation, or compliance monitoring.
2. Accelerated processes: Shortening cycle times for critical operations, from onboarding new customers to processing insurance claims or managing financial reporting.
3. Enhanced employee experience: Freeing human workers from tedious, complex coordination tasks allows them to focus on higher-value strategic work, innovation, and customer interaction.
4. Meaningful business growth: Enabling new services or faster responses that were previously unfeasible due to process complexity or cost.

Unlike basic automation, which often yields incremental improvements, agentic automation can fundamentally redesign how work gets done, driving transformative efficiency.

Complementing, not replacing: Integrating agentic AI with existing systems

A key concern for IT leaders is potential disruption from new technologies. Agentic automation should complement, not replace, existing investments. RPA robots can continue managing high-volume, rules-based tasks, supervised by AI agents.

The UiPath approach, for example, builds upon its established automation platform, allowing agentic capabilities to be layered onto existing workflows. An AI agent might manage the complex decision-making and exception handling within a process, triggering RPA robots for specific sub-tasks or interacting with human employees for necessary approvals or inputs. This ensures that organisations can leverage the power of agentic AI without abandoning their current automation infrastructure

The autonomy that makes agentic AI powerful also necessitates robust governance and orchestration. Unleashing autonomous agents without clear oversight, monitoring, and control mechanisms poses significant risks, from operational errors to security vulnerabilities and compliance breaches.

Frameworks are crucial in agentic automation. They must offer human oversight, enabling transparent control, approvals, and intervention. Monitoring and logging systems are essential for tracking agent actions and decisions. 

The framework should also more efficiently manage interactions between AI agents, RPA bots, human workers, and enterprise systems. Finally, security and compliance measures must ensure agents operate within defined boundaries and adhere to organizational policies and regulations.

Introducing the UiPath Agentic Automation Orchestration

UiPath is addressing these needs directly with its Agentic Automation platform. Designed as an orchestration layer, it aims to provide the necessary governance, visibility, and control over the entire workflow, including agents, robots, and people operating within the enterprise. 

By leveraging the core UiPath Platform, it seeks to integrate agentic capabilities seamlessly, ensuring that autonomous operations align with business rules and compliance requirements. This framework is positioned not just to deploy agents, but to manage the entire ecosystem of automated and human work responsibly.

The most crucial factor for successful adoption is ensuring that agentic automation can be integrated without placing undue strain on existing IT systems or requiring massive re-architecting projects. The goal is accessibility. Platforms that offer low-code development environments, pre-built connectors for common enterprise applications, and robust API integration capabilities are vital.

UiPath’s strategy focuses on embedding agentic features within its familiar platform, aiming to lower the barrier to entry. This allows IT teams to start experimenting with and deploying agentic automation for specific high-value use cases, leveraging their existing skills and infrastructure investments. The focus is on delivering the productivity benefits of agentic AI as smoothly and non-disruptively as possible, integrating with the complex reality of modern enterprise IT.

Moving towards intelligent, autonomous operations

Agentic automation represents a leap forward, moving beyond task automation to achieve complex business outcomes autonomously. Realising this potential requires purpose-built platforms that enable seamless integration, robust governance, and effective orchestration.

For businesses and IT leaders navigating the era of AI integration, exploring agentic automation frameworks like UiPath's offers a way to harness the power of autonomous systems for productivity, savings, and growth, while maintaining control and complementing existing technology. The future of automation is increasingly intelligent and autonomous, requiring a strategic, governed approach.