The future is agentic AI: Power it with Agent Workbench

A pivotal shift is underway: agentic AI is here, and it’s full of opportunity. Enterprises that embrace it stand to secure a significant competitive advantage and build upon their AI success. In fact, 74% of organizations report that AI is already increasing productivity and improving their organization’s overall performance. Just imagine how much more impact agentic systems that augment human expertise and deliver true end-to-end automation could have. With 93% reporting they are already developing—or plan to develop—their own custom agents, it’s clear organizations are eager to tap into the limitless potential of agentic AI.

Going from pilot to full-scale enterprise production isn’t easy, though. Bringing these agentic systems to life requires specialized resources and can introduce new risks. To make matters worse, the market is saturated with thousands of AI tools that promise impact, but few actually deliver, leading to increased fragmentation and sprawl. It’s no wonder 90% of organizations report that their core agentic use cases remain in pilot mode.

If you’re stuck in a proof-of-concept rut, it’s time to meet the game-changing solution you’ve been waiting for. OutSystems Agent Workbench empowers you to create custom agents that streamline operations, elevate experiences, and grow revenue, all on the AI-powered low-code platform made for enterprise innovation. And you can do it faster, easier, and more securely than you ever thought possible.

Before diving into more detail on Agent Workbench, let's review what agentic AI is, how it differs from generative AI, and the benefits of a unified platform approach.

For example, you could create an HR agentic system that screens applications, schedules interviews, and tailors onboarding plans—enabling recruiters to focus on more strategic hiring decisions.

And that’s just one use case. Our recent survey with KPMG and CIO Dive reveals the ways organizations are looking to apply agentic AI across their core business functions:

• 60% plan to automate internal business processes.
• 61% anticipate using it for code reviews and quality assurance.
• 77% are planning to implement AI agents for IT workflows, including proactive system monitoring and incident reporting.
• 49% intend to use AI agents in customer support portals.

What is the difference between agentic and generative AI?

Generative AI and agentic AI are closely related but have distinct capabilities. Generative AI responds reactively to user prompts and creates content, such as text, images, or code, based on patterns in data. Agentic AI takes this a step further by making decisions, taking actions, and pursuing goals autonomously.

Generative AI enhances agentic AI by producing the language, code, and content agentic AI systems need to act. It supports any agentic-AI-driven task requiring content generation and will remain a critical part of your broader AI strategy. Compare agentic AI and generative AI in more detail.

What are AI agents?

AI agents are AI-driven components that are built to handle business tasks like processing data, responding to customer inquiries, executing workflows, or solving problems. To be truly defined as an agent, it needs to have autonomy and decision-making power. Learn more about what makes agentic AI truly agentic in this blog.

Taking a unified platform approach to agentic AI

As more enterprises start to move beyond pilot phases, going to production with human-AI collaboration poses significant challenges around security, data accessibility, and operational complexity. In fact, 44% of software executives said they believe increased technical debt and AI sprawl are top risk areas.

That’s why leading enterprises are adopting a unified platform strategy—and why you should consider it too. By centralizing agent development and orchestration in a single platform, you can reduce redundancy, increase oversight, and eliminate the risk of AI agent sprawl.

For enterprises looking to quickly and securely operationalize agentic AI, an AI-powered low-code platform offers the most effective path forward. By abstracting technical complexity, teams can build and deploy agents, no new skills or additional resources needed. Visual development accelerates delivery, composable components ensure reusability, and built-in controls support compliance and scalability—helping you achieve AI-driven outcomes faster without the constraints of standard development.

Meet OutSystems Agent Workbench: Fuel enterprise innovation with custom agents

With OutSystems Agent Workbench, you can enhance experiences and automate processes by creating custom agents that deliver real results—and do it all with your current team:

• Shift to AI-first transformation—with agentic AI innovation made simple: With the power of AI and low-code, you finally have the holistic solution you need to innovate and transform your business processes into intelligent agentic systems faster and easier than ever before! Plus, you get the flexibility you need to pivot quickly.
• Go from build to deploy—with agents you can trust, govern, and scale: No risky business here! Maintain full oversight and governance over every AI-driven process and enforce strict access controls and guardrails to ensure agents operate safely and predictably.
• Put agentic AI to work everywhere—with total control and no sprawl: With a complete agentic AI toolset integrated in a single platform, you can seamlessly scale intelligent agents without fragmented tools or additional maintenance costs.

Agent Workbench includes robust feature sets for AI data and model integration, AI agent lifecycle management, and AI agent orchestration, which ensures you have everything you need to power your AI strategy and do it right from the start! Let’s take a closer look.

AI data and model integration: Build a future-proof AI foundation

Most organizations struggle to operationalize agentic AI because their data is siloed and there’s no easy way to connect AI models to their core systems. Without unified access to data and AI models, agents can't reason effectively or act with the context they need to deliver real value.

Agent Workbench’s AI data and model integration features change that, enabling you to configure a foundational layer of large language models (LLMs) and data to fuel agent action and decision-making. You can unify access to third-party and custom AI models as well as enterprise knowledge sources—both structured and unstructured—to help you accelerate development, scale AI solutions with ease, and future-proof your AI strategy.

Take this real-world scenario: to streamline procurement, a company wants to use agents to review contracts, ensure compliance, and suggest next steps. With OutSystems, agents can:

• Access structured data like vendor records and purchase history through OutSystems Data Fabric
• Retrieve and interpret unstructured content such as contracts and policies through integrated knowledge sources
• Use internal models and third-party LLMs through a central model catalog

Because the data and AI models are integrated at a foundational level, the agent doesn’t just pull info—it understands it, applies policy logic, and takes informed action autonomously.

AI agent lifecycle management: Deploy faster, manage smarter

Generic off-the-shelf AI agents often fall short because they don’t reflect the unique workflows, data, and goals of your enterprise. But building custom agents from scratch while ensuring scalability and reliability can be time-consuming, complex, and require specialized skills. That’s why many enterprises stall during the pilot phase.

This is where Agent Workbench’s AI agent lifecycle management capabilities shine: you can create, deploy, and monitor complex agents with AI-powered low-code agility. This simplifies the entire agent lifecycle, eliminating the need for mountains of code. With full control and visibility over agent performance, usage, and compliance, you can move from pilot to full-scale production in record time.

Here’s an example: instead of using a generic chatbot, you can build a custom return agent that checks order status and validates return eligibility—resulting in faster customer resolutions and reduced manual effort.

AI agent orchestration: Enable human-AI teamwork at scale

Most organizations struggle to scale AI automation because individual agents operate in silos or require constant human oversight. This fragmentation slows delivery, increases risk, and limits impact.

With Agent Workbench’s AI agent orchestration features, you can coordinate multiple agents across workflows—whether working side-by-side, in sequence, in hierarchy, with or without humans in the loop—to drive new levels of business value and ROI. You gain centralized control, faster automation, and stronger compliance across all of your agentic systems.

For example, you can coordinate agents to team up and streamline procurement—one extracts invoice data, another checks contract terms, and a third routes approvals, all working seamlessly in sync.

Learn more about Agent Workbench in this video.

What use cases does Agent Workbench support?

Good question… OutSystems enables you to create and orchestrate agents for literally ANY use case. I’ve shared a few examples already, but because OutSystems takes a BYOA approach, where you can “bring your own AI models and agents” as well as “build your own agents” precisely tailored to your business, there are no limits on what you can do:

• Connect to any AI model.
• Use any data source.
• Integrate any agent from anywhere.
• Deploy agents across any department, workflow, or data.
• Orchestrate human-agent teamwork at any scale.

So whether your goal is to boost productivity or enhance the customer experience, you can do it all using the core systems, AI models, third-party agents, and team you already have in place. In fact, 63% of organizations are already planning to use agentic AI to personalize customer experiences by integrating automated decision-making workflows into their user-facing apps.

Curious how leading organizations plan to scale their agentic AI efforts beyond the customer experience? Check out our report on navigating generative and agentic AI with CIO Dive and KPMG.

Empowering the future of app and agent development

The introduction of OutSystems Agent Workbench is a major leap forward. From point solutions that can’t integrate or scale to bulky systems that silo processes and slow things down, OutSystems is the only platform that brings you a complete and unified agentic AI solution without complexity or risk. And you don’t need an AI team to get started—just a platform purpose-built to support any enterprise AI use case now and in the future.

Whether you’re a current customer that needs to deliver agents and agentic systems faster using the combined power of AI and low-code or someone looking for a better, easier way to scale agents enterprise-wide, OutSystems Agent Workbench is here to help. Learn more about Agent Workbench by exploring the product page.