Enterprise Guide to Agentic Automation

At the enterprise level, AI adoption has been swift: as of 2025, 99% of enterprises have integrated AI into their operations in one way or another.

That number shouldn’t come as a surprise. While the buzz around generative AI tools like ChatGPT is still ongoing, businesses have been leveraging AI-driven automation for a while now. For example, marketing teams have been using Google’s AI-powered Performance Max campaigns since 2021 to automatically optimize paid search campaigns, and AI-powered chatbots have been helping to field customer queries since the 2010s.

But while AI automation may be mainstream, only 31% of enterprises are actively planning for the next frontier: agentic automation.

Agentic automation goes beyond AI automation by using AI-driven agents to make decisions and carry out tasks autonomously, without the need for human intervention. In this guide, we’ll explore how it works, as well as strategies for getting started with agentic automation at the enterprise level.

What is agentic automation?

Agentic automation is the orchestration of AI agents to accomplish business tasks with minimal human intervention. Agentic systems go beyond automating individual tasks to enable true end-to-end process automation.

Unlike traditional rule-based automation tools, agentic automation is goal-oriented. These goals are set by humans, but the agents do the rest — collecting data, interpreting it and acting on it — all on their own.

That doesn’t mean humans are out of the picture, though. With oversight and feedback, AI agents are able to learn, adapt and improve over time, boosting the efficiency of agentic systems.

What are AI agents?

An AI agent is an advanced AI system that is capable of:

• Operating without constant human prompting or supervision
• Interpreting goals and executing complex tasks to achieve them
• Solving problems and making recommendations
• Making decisions and self-learning
• Interacting with both external and internal environments, including systems, data sources, applications, APIs and other AI agents

Agentic automation happens when these individual agents collaborate and are integrated across business systems. Enterprise integration solutions like iPaaS (Integration Platform as a Service) automate connectivity between applications and data sources, making it easier to deploy AI agents at scale.

What’s more, iPaaS solutions themselves are increasingly leveraging AI to make it easier for both technical and non-technical users to create and manage integrations.

AI Agents vs AI Assistants vs Generative AI

Generative AI (genAI) is the foundational layer that makes AI agents and Agentic AI possible. It provides the core capabilities of language understanding, reasoning and contextual generation that agents use to interpret goals, plan actions and produce intelligent outputs.

AI agents build on this foundation by adding tools, memory and autonomy to act in the real world,. Agentic AI goes a step further, using generative reasoning to self-direct, learn and coordinate across complex goals and environments.

AI agents are more advanced than AI assistants and generative AI (genAI) tools like ChatGPT. But for organizations planning their AI strategy, it’s not a matter of which is best—it’s about strategically applying different AI technologies to maximize their value.

The chart below breaks down the key differences between AI agents, AI assistants, genAI, and traditional automation so that you can assess where each tool might fit in with your overall agentic automation strategy:

How agentic AI powers intelligent automation

Agentic automation combines autonomy, learning and orchestration to handle sophisticated workflows that once required human oversight.

Autonomous decision making

AI agents evaluate options, weigh trade-offs and act toward specific goals without waiting for instructions. This capability reduces manual decision points and accelerates response times across the business.

Continuous learning

Unlike traditional bots, agentic automation systems continuously analyze results and refine their behavior. Each completed workflow becomes a data point that helps improve agents’ accuracy and performance over time.

Data orchestration

Agentic systems excel at bringing data together from multiple sources. When AI agents are fully integrated within the enterprise, they can synchronize customer, financial or supply chain information across platforms — ensuring every department works from a single source of truth.

Complex workflow management

With agentic process automation, enterprises can connect hundreds of processes that once operated in isolation. Agents monitor dependencies, trigger related tasks and collaborate with other agents to manage multi-step operations end to end.

Agentic automation use cases

Agentic automation can be applied across multiple departments to improve efficiency, accuracy and collaboration. Some of the most high-impact enterprise use cases include:

Sales

AI agents can surface account insights, prioritize leads, and manage updates between CRM, analytics, and marketing platforms. This helps sales teams focus on strategy instead of repetitive data entry. They can also recommend next-best actions or alert reps to deal risks in real time, creating more proactive, data-driven sales cycles.

Customer Service

Agents can respond to inquiries, summarize customer histories and route tickets based on intent. The result is faster response times and more consistent support experiences. By handling common requests instantly and escalating complex issues with full context, agents free support teams to focus on higher-value, relationship-building interactions.

HR

From onboarding and training to IT provisioning, AI agents streamline repetitive HR tasks and ensure every new hire has what they need from day one. They can also manage ongoing activities such as compliance tracking, benefits updates and employee surveys, giving HR teams more time to focus on engagement and retention.
Learn more about the Jitterbit HR Agent

Knowledge Management

AI agents can instantly locate and share information from documents, databases and enterprise systems. This eliminates data silos and ensures employees can access reliable insights when they need them most.

Over time, agents learn which resources are most useful, continuously improving how information is categorized, retrieved and shared across the organization.

How to get started with agentic automation

Is your business part of the 31% actively planning for agentic AI? If not, here are some tips to help you get up to speed:

Start with a simple, practical use case

Choose a routine, measurable process that can deliver quick results. Automating a simple task — such as report generation, employee onboarding or data synchronization — helps teams build trust in the technology before moving on to more complex workflows.

Pre-built AI agents are an effective starting point because they come ready to deploy and can be easily customized for your specific needs.

Measure twice, cut once

Map out your goals, inputs and dependencies clearly so your AI agents understand how to act and when to intervene. Establish monitoring tools and governance structures early to ensure accuracy, compliance and accountability.

Test and improve

Monitor results closely, gather feedback from users and adjust parameters to enhance performance. Over time, your AI agents will learn from each cycle, becoming more efficient while helping your team uncover new opportunities for improvement.

Don’t neglect the human factor

Technology performs best when it complements human judgment. To get the most from agentic AI automation, involve your teams in setting goals, defining success criteria and reviewing results.

This approach prevents over-reliance on automation while also avoiding underuse. When people understand the purpose behind the process, adoption is faster and more effective.

Embed AI agents into existing apps

Integrate AI agents into your existing applications and workflows instead of replacing entire systems. This ensures a smoother transition, reduces disruption and helps employees adapt naturally.

Over time, embedding agents within familiar tools creates a unified environment where automation enhances productivity without adding complexity.

Unlock the power of agentic AI with Jitterbit’s enterprise automation platform

Jitterbit Harmony isn’t just an integration platform.It’s an AI-infused enterprise automation platform that brings together iPaaS, agentic AI, application development and API management in one unified, scalable solution. With Jitterbit, businesses can:

• Deploy, govern and scale AI agents in a platform that prioritizes enterprise-grade security, compliance and governance
• Kickstart agentic automation with pre-built, enterprise-ready AI agents for sales, HR and knowledge management available in the Jitterbit Marketplace
• Work with agentic AI professionals to design custom agents for any use case

Learn more about how we’re helping businesses achieve agentic automation at scale, or get in touch with a product expert to schedule a demo.