Getting started with agentic automation: What executives need to know

The recent flurry of AI news signals one thing: AI models are getting commoditized, becoming more advanced but cheaper to use. The opportunity, and necessity, for business leaders to leverage these models is growing exponentially. But how can they make the most of these AI innovations as they happen?

Agentic automation is crucial for adopting and scaling game-changing AI across any organization. AI models are powerful, but they lack utility as a standalone technology unable to integrate with business systems or take direct action. Fortunately, agents—AI-based entities able to work independently or supervised by people—can call on and use these models as effective tools. In agentic automation, AI agents work alongside robots and humans, leveraging AI to automate complex, end-to-end processes and unlock transformative enterprise value.

UiPath research shows 37% of IT leaders in the United States (U.S.) are already seeing the value of agentic AI, while 97% are interested in using the technology. However, executives must approach adoption carefully to guard their core business data and ensure predictable execution from their agents. Here are the top considerations business leaders should make before getting started with agentic automation:

Agentic automation: to build or not to build?

Organizations have the choice of adopting pre-existing agent architectures or building them from scratch. However, do-it-yourself agent frameworks are deceptively complicated, often requiring advanced coding and machine learning skills. Controlling the level of autonomy, or agency, of agents is also critical. Businesses need AI agents that provide predictable, trustworthy results. But developing the necessary guardrails and monitoring capabilities can be a costly investment.

For most enterprises, adopting an existing agent framework is the best option. These are characterized by low-code agent development tools that help employees build custom agents quickly and safely. They provide capabilities to instruct and evaluate agents, integrate them with enterprise systems, create custom datasets, and fine-tune specialized models as well as embeddings. Purchasing an existing agentic automation solution combats infrastructure sprawl and saves incremental costs by providing all these capabilities in one place.

Combining specialized agents with enterprise-grade tools—orchestrated in workflows with deterministic robots and humans in the loop—results in accurate and reliable agents. In this way, leveraging an existing platform with built-in governance and controls advances your agentic execution rapidly without compromising on safety or security. But how can executives identify the best platform for their business?

The agentic buyer’s guide

Executives need to consider a wide range of factors when selecting an agentic automation solution. However, as an emerging technology, there are several unique and critical considerations that should be made: 

Enterprise tools

AI agents are only as useful as the tools they can use. Consider not only the agents, but their access to integral enterprise capabilities like UI and API automations, intelligent document processing, and connectors for the latest and greatest AI models. These are vital for automating complex processes end to end. 

Human in the loop

Humans are core to exception management in agentic automation, solving the challenges that agents can’t fix with AI or automation. Human in the loop must be a built-in feature, enabling escalation and reviews of critical customer-facing processes to be easily built into workflows. Ensure you have visibility into the quality of agent execution, and the assurance that agents learn from these interactions. You should give your agents greater autonomy as they learn and improve, but the decision should be based on proven execution rather than wishful thinking. 

Low-code development

Prebuilt agents for core enterprise processes can give you a head start and generate quick value. But businesses also need the tools and infrastructure to rapidly customize or build specialized agents tailored to their specific context. Many hyperscalers offer complex products that can only be used by developers, but enterprises scale best with low-code platforms that ordinary employees can use. In this way, a low-code development environment helps to democratize the development process and rapidly scale agentic automation across the enterprise. They keep technical debt under control and allow the business to focus on its strategic initiatives. 

Vendor agnostic

Technology leaders across the board are offering their own AI agents, ready to be deployed and used by employees. However, these will be most useful within their own restricted vendor ecosystems. Buyers should instead prioritize vendor-agnostic solutions that won’t reduce their flexibility or lock them out of vital AI developments or capabilities in the long run. 

End-to-end orchestration

The enterprise is messy, and agents are only one part of the solution. AI agents require access to various tools, people, and even other agents to automate long and complex processes. To achieve business outcomes, enterprises benefit from solutions that let them model, orchestrate, and monitor end-to-end complex processes across all these components. This requires a complete orchestration platform.

Choosing a platform for agentic orchestration

An orchestration platform, or layer, sits at the top of agentic automation. Indeed, one can’t exist without the other. Effective agentic orchestration ensures AI agents, models, and people connect and collaborate smoothly and work within your trust and data boundaries. Business leaders should consider the following when evaluating an orchestration solution: 

Enterprise-grade quality and accuracy

Agentic automation is an orchestra, and AI agents don’t play alone. To ensure performance and accuracy, your chosen solution must provide enterprise-grade infrastructure, with best-in-class automation and AI capabilities to deliver value faster and at scale. You could assemble these capabilities piece by piece, but gradually and at great cost. It’s much better to leverage a solution with built-in, first-class AI and automation. 

Management and monitoring

Continuous monitoring and improvement are core to agentic automation, helping your agents to correct mistakes, learn, and adapt more quickly. Enterprises should seek out solutions that enable the automation, modeling, and monitoring of complex business processes from start to finish. Features such as run-time visibility, real-time alerts, and version control are crucial for monitoring and improving your agents. 

Governance and trust

Whether you’re in the cloud or on-premises, the security of all data associated with your agentic automation projects needs to be protected. Ensure your chosen solution delivers transparency, trust, and control over the interactions between your agents, organizational data, as well as first- and third-party AI models. The best practice is to have a dedicated trust layer, with strong access controls, real-time analytics, and detailed reports on how AI is being used across your business processes.

UiPath offers a comprehensive solution for agentic automation and orchestration, combining controlled agency, enterprise-grade tools, and end-to-end orchestration. Our low-code development environment enables efficient agent creation, while built-in human in the loop capabilities ensure accuracy. We pioneer a vendor-agnostic approach, empowering you to integrate the tools your business needs, avoiding lock-in by enhancing flexibility. With advanced quality assurance, monitoring, and governance features, UiPath empowers organizations to drive agentic automation at scale—with control, compliance, and confidence.

To see how UiPath delivers on agentic automation and orchestration, register now for the UiPath Agentic AI Summit.