Adopting agentic AI in 2026: 5 things you can do right now

You might be heading into 2026 thinking “Okay, this is the year I finally get AI to really work for my business.” Yet, with the rise of AI agents and AI innovation moving faster than ever, it’s getting harder to keep up.

And you’re not alone. Many enterprises are still figuring out how to adopt agentic AI in a way that actually scales and delivers measurable business impact. Recent studies from Accenture and Wipro show that 70-80% of agentic initiatives haven’t made it to enterprise scale.

But that’s not stopping organizations from pressing ahead. According to NTT, Inc. and WSJ Intelligence, 68% of global CEOs plan to increase AI investment in the next two years.

The good news is that agentic AI success isn’t a distant vision. UiPath customers like Pearson, Allegis Global Solutions, and SunExpress are already seeing meaningful results.

And there are concrete actions you can take today to set yourself up for real success with agentic AI in 2026 and beyond. We’ve pulled together five of the most important steps to help you get started:

1. Unlock the data trapped in documents and communications

Every process in your organization runs on documents: invoices, contracts, emails, service requests, patient forms, purchase orders, customer communications…the list is endless. They carry essential business context, but most of that context lives in unstructured, or partially structured formats that are hard for AI agents to use.

Agentic AI can’t perform with accuracy or confidence if the data fueling it is incomplete or unreliable. That’s why a critical early investment is intelligent document processing (IDP): extracting and structuring the data trapped inside your documents so it can be used by AI agents and drive automation.

This step pays off in two ways:

• It enriches the data foundation your agents rely on, so they can understand what needs to happen next in a process

• It eliminates a massive amount of manual document processing work today, freeing teams to focus on higher-value activities

The better your document data quality is now, the more capable, accurate, and compliant your agentic AI will be later.

Download "The definitive guide to intelligent document processing."

2. Start experimenting with AI agents now

Most organizations aren’t starting from scratch; they already have a foundation of enterprise automation running across finance, IT, operations, HR, and customer service. The opportunity now is to extend what those automations can do with AI.

AI agents enhance automation with intelligence, flexibility, and adaptability. They interpret data, make decisions, adapt to different scenarios, and take action across systems. They open the door to entirely new use cases that weren’t possible before.

However, accessibility and experimentation are crucial. Different teams—and even different use cases—need different approaches.

Give your teams a low-code, guided way to build, test, and publish AI agents safely. Business technologists and automation developers can spin up agents quickly, test ideas, and validate value without needing to write code.

When your job-to-be-done requires specialization—deep system integration, custom logic, advanced reasoning, or enterprise-grade performance—engineering teams can build agents programmatically using SDKs and extensions. They get full flexibility without losing the safety, governance, and orchestration of the broader platform.

Encourage a culture of curiosity: What could a collections agent do? A procurement agent? A customer onboarding agent? A cybersecurity triage agent? The organizations that experiment now will enter 2026 not with theoretical ideas, but with working agent prototypes, real learnings, and a clear sense of where AI creates the most value.

3. Design and orchestrate your processes with agents in mind

Adopting agentic AI isn’t just inserting an agent into a single process step. To unlock transformational value, you need to reimagine what the end-to-end process could look like when decisions are automated, actions orchestrated, and workflows can adapt in real time.

This is where process optimization and agentic orchestration come into play.

Before you deploy agents, review your processes and model the ideal state. Identify the gaps, expected handoffs, areas that still require human judgment, and moments where an agent could accelerate execution or improve accuracy. This creates a cleaner, more intentional foundation for agentic automation.

With an optimally designed process, you can then orchestrate in a unified and intelligent way. A strong orchestration layer gives you visibility and control across your workflows, so exceptions are resolved quickly and work keeps moving. Orchestration turns a well-designed process into one that consistently performs at scale.

Watch how agentic orchestration enables ROI at enterprise scale:

Designing processes with agents in mind helps you avoid unnecessary complexity and prevents agent sprawl—the proliferation of disconnected agents across an organization without unified visibility, controls, or governance. This risk of agent sprawl grows as teams begin building more autonomous systems.

Organizations that take the time to audit, model and orchestrate their processes will get far more value from agentic AI, and they’ll be able to scale faster with fewer growing pains.

Download "The ultimate guide to agentic orchestration."

4. Use process intelligence to understand where agents fit

Before you ask where to introduce agentic AI, ask a more important question: where is my process actually struggling?

Process intelligence provides a data-driven view into inefficiencies, bottlenecks, rework loops, compliance risks, and the true cost and duration of workflows. With that visibility, you can pinpoint exactly where AI agents will have the greatest impact.

The goal is not agentic AI on its own. The goal is better processes, better outcomes, and better operational performance, enabled by agentic capabilities.

When you understand your processes at a granular level, every agent you deploy becomes more targeted and more valuable.

Above is a quick look at the combined value of process intelligence and agentic orchestration. See the entire infographic.

5. Put AI governance in place before you scale

Every leader wants to move fast with AI, but the moment you scale, governance becomes a non-negotiable. AI agents interact with sensitive data, make decisions that affect people and outcomes, and often perform tasks that were previously handled by people. Without governance, you risk inconsistency, compliance issues, and slower adoption across the enterprise.

Strong AI governance allows you to:

• See exactly how AI models are being used

• Track what data they can access and under what conditions

• Understand how decisions and outcomes are generated

• Set standards for approvals, access controls, transparency, and auditability

• Ensure employees use AI responsibly and consistently

Done right, governance isn’t a barrier to innovation. It gives leaders the confidence to scale agentic AI widely and safely, and empowers teams to innovate boldly.

Read what IT leaders look for in modern AI governance.

Lay the groundwork today to achieve your 2026 goals

The organizations that win with agentic AI in 2026 and beyond are the ones taking small, intentional steps right now. When you strengthen your data, try out early use cases, embed orchestration, and put the right guardrails in place, you are setting up your teams and your future agents to thrive.

The UiPath 2026 AI and Agentic Automation Trends Report is more than a trends report. It’s your map to the future of intelligent, governed, agentic enterprise.

Unlock the map—download the report now.

And join us tomorrow for the 2026 AI and Agentic Automation Trends webinar. The webinar goes beyond the trends report, with added insights from UiPath agentic experts.

Can't make it? Be sure to register for the webinar and following the event, we'll email you a link to the on-demand recording to view at your convenience.