OutSystems Agent Workbench
When enterprise IT leaders first began to embrace low-code software development back in the mid-2000s, they measured the time savings in hours per developer. Today, they are measuring improvements in time to market, in business agility, and in customer experience. How much more could your organization do if you could get a decade’s worth of software to market in one week? In one day?
Welcome to the “agentic AI enterprise,” where developers and other creators can build autonomous AI agents for every task and customer interaction, and agents actively participate in business processes, reason, and collaborate with humans. The agentic enterprise is an intelligent ecosystem that capitalizes on the strengths of people and machines, without the constraints on capacity that have historically limited innovation.
If you think this is some kind of future state, think again. In a 2025 survey of 1000 U.S. business executives, one in five executives report using AI agents to automate customer support, streamline supply chain operations, and personalize customer experiences at scale.
But this is just the beginning.
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Agentic AI is moving quickly
The conversation around agentic AI is moving quickly from “how would we use agents?” to “what couldn’t we do with agents?” Take TravelEssence, for example. After experimenting with agentic AI and implementing two agents, the company realized that agents can address more use cases than they first thought. Now it has adopted OutSystems Agent Workbench and is creating a “swarm of AI agents” to accelerate the delivery of tailored travel recommendations for its clients.
What does this mean for IT leaders who now must manage a proliferation of autonomous workers and dynamic agentic processes in their portfolio? Remember, agents are software too, with all the same potential for errors, security gaps, and governance concerns (but exponentially magnified). As with any accelerated and automated process, from traditional manufacturing to smart factories or human-led customer service to virtual agents, for example, we have new and far-reaching responsibilities to manage the full lifecycle of agentic apps and systems.
Here are some strategies we are offering our customers to plan a successful and sustainable agentic transformation.
Navigating the journey to the agentic AI enterprise
In an agentic AI enterprise, AI removes obstacles that slow human teams down. When grunt work, context switching, disparate communications, and unnecessary complexity are shifted to agents, everyone has more time to ideate, iterate, and innovate. This creates a positive cycle where more efficient processes and better customer and employee experiences lead to new insights, creating opportunities for even more innovation.
Simply adopting agentic AI is not a straight path to becoming an agentic enterprise, however. Today, most organizations are adding agents to an already fragmented landscape of apps and data. Many everyday productivity apps and SaaS platforms include AI agents now and some invite nontechnical employees to build their own. Marketing builds chatbots on one platform, operations uses a different framework for process automation, and customer service deploys agents through yet another vendor. Soon you have a collection of isolated AI experiments that can't share data, can't be governed consistently, and create more problems than they solve.
IT leaders should resist the temptation to restrict agentic AI experimentation. Instead, they should establish a system for full portfolio visibility and governance that works with this reality and assumes that it will continue to evolve in unpredictable ways. The goal should be to design agentic systems where humans and AI complement each other, with human-on-the-loop flows that give people final control. AI handles the heavy lifting on data processing and routine decisions. Humans provide additional strategic insight on patterns that AI has not encountered and oversight for complex or sensitive situations.
Ultimately, the heroes of the agentic AI enterprise will be the strategic leaders who build a foundation for rapid prototyping and iteration not as a siloed R&D initiative, but as a fully integrated innovation engine within their current operations. This means empowering teams to experiment with different LLMs and build agents that connect to your existing applications, workflows, and data. In this way, the agentic enterprise is an organic, living ecosystem that evolves for the demands of the future by using and improving on what is already working.
Land immediate agentic AI impact, then expand
Companies are holding off on enterprise-wide AI deployment because they believe that making agentic AI a core part of business and IT is a major undertaking. But waiting has an opportunity cost, not just in terms of the inevitable AI sprawl, but also the risk of disruption by their competitors who use agentic AI to launch new products and services faster. Forward-thinking leaders are taking an iterative approach: identifying specific use cases where AI agents can make an immediate impact, prototyping and testing, then expanding from there.
Another belief is that agentic AI demands we leave behind the applications and data already in place. In reality, your legacy systems, CRM, ERP, and custom applications are valuable assets that significantly increase the value of your AI agents. The technology already exists to harmonize historical and real-time data stored in different repositories and formats to be used by agents, while also making sure that the surface exposed to AI is limited to the context of a given agent interaction.
Fears about runaway costs with agentic AI are also misplaced. The cost equation is straightforward when you approach it correctly. You track how many tokens each agent consumes, understand the cost per token based on your AI provider contracts, and measure that against the outcomes the agent delivers. It's similar to traditional resource management, just with a new type of resource.
Use a unified platform for the full lifecycle of agentic AI
It is early days in the agentic software revolution, and with the technology evolving at astonishing speed, many organizations are experiencing runaway agent sprawl. IT teams are having to determine how to manage a heterogeneous portfolio of agentic apps that includes custom-built apps and agents. While several AI vendors are offering agent orchestration layers, they are limited to those built with their products.
What is needed is a platform that provides a unified view of all agents, their lineage, and their decisions. When five linked agents are handling their tasks, a change to the first one could have exponential impacts on the fifth. Or consider the situation where an agent depends on data from a specific system and then the data structure changes or evolves. It’s possible that, with such a brittle system, the change could break the input the agent expects. You need full visibility across agents, experiences and data, in a lifecycle that supports continuous change so that no agents or systems are broken. A unified platform can provide that view, while tracing the chain from end to end to make sure you always understand and improve the full process.
The same principles that made low-code software development platforms a strategic foundation for agile enterprises apply to the agentic AI enterprise:
- Visual, model-driven tools that simplify and speed up the creation phase
- Modular components that can be reused and updated
- Capabilities that fully trace and monitor performance
- Workflows that enable accountability
- Tools for filtering, restricting, and securing data
The powerful combination of accelerated AI-driven development with guaranteed performance is what makes Agent Workbench stand out in a crowded field of AI app and agent generation tools.
Support your transformation to an agentic enterprise with OutSystems
At OutSystems, we’ve built Agent Workbench to simplify the path to becoming an agentic AI enterprise. Part of our unified approach to application and agent development, Agent Workbench makes it easy for any IT team to create, deploy, and manage AI agents that integrate with existing systems and deliver measurable business value.
The OutSystems AI-powered low-code platform handles the complexity of agent lifecycle management, from development and testing to deployment and monitoring. Teams can create agents that connect to any data source, work with any AI model, and integrate into existing applications and workflows.
Most importantly, it's designed to work with what you already have. Your data, your applications, your team's existing skills. You're not starting from scratch or learning entirely new development approaches.
Your agentic AI future is here
The agentic enterprise isn't a distant future concept. Nor is it about AI that can write an email for you. It's about empowering AI to solve problems so you don’t have to write emails to address or explain them. OutSystems has brought your data, your systems, your people, and AI together in a platform you trust.
Join us as we walk together towards this future.
Discover how innovative organizations are transforming with agentic AI in “Agents of Change,” and get started with Agent Workbench.
