Software robots have freed businesses from repetitive tasks. AI agents, meanwhile, are poised to free humans from simple decisions.

After RPA, here comes the era of Agentic AI.

Tools such as Composio, n8n, Flowise and OpenAI's Agent Builder mark the emergence of a new wave of automation: intelligent agents capable of understanding context, acting within business systems and adapting to unpredictable situations. But do these tools really represent the new RPA? And above all, are they mature enough for critical business processes?

From RPA to AI Agents: Understanding the Paradigm Shift in Automation

RPA tools such as UiPath, BluePrism and Automation Anywhere were designed to mimic humans in defined, stable processes: clicks, forms, extractions, transfers.

Generative AI, on the other hand, introduces a radically different paradigm:

• Actions are no longer hard-coded; they are driven by context and language comprehension.
• Workflows can adapt dynamically to intentions and results.
• Automation becomes intelligent, capable of making decisions, not just executing rules.

This transformation is giving rise to what some are already calling AI Agents or Cognitive Workflows.

Composio, n8n, Flowise: Tools for intelligent automation with AI agents

Composio

Composio is an open-source platform that connects LLMs (GPT, Claude, Mistral, etc.) to third-party applications through standardised ‘actions’.

The idea is to give AI agents concrete powers, such as sending an email, creating a Jira ticket, querying an SQL database, triggering an ML pipeline, and more.

It bridges the gap between language models and the real world with a modular, secure and extensible approach.

Composio stands out for:

• A ‘connectors + actions’ architecture similar to Zapier for AI,
• An open source philosophy,
• An SDK for creating your own custom actions,

Native integration with LangChain, LlamaIndex and CrewAI.

Agent Builder (OpenAI)

With Agent Builder, OpenAI takes the logic of ‘agentic AI’ even further by directly integrating a framework for creating and orchestrating agents on top of its GPT models into its ecosystem.

The idea is to enable any user, technical or otherwise, to design a specialised agent capable of using tools, reasoning in a broad context and interacting with external sources (APIs, files, databases, etc.).

This approach marks a fusion between AI platforms and automation: where RPA required scripts and an execution environment, an OpenAI agent can be configured and deployed in minutes, with integrated memory, action and conversational context management.

But this power has a downside: Agent Builder is proprietary and centralised.

Issues of sovereignty, auditability and dependence on the OpenAI ecosystem quickly arise.

Digital services companies and IT departments committed to open source and control over their data flows will prefer solutions such as Composio or CrewAI, which offer local control and full interoperability.

n8n

n8n, already well known for its no-code workflows, is moving into the same territory: it now allows you to orchestrate hybrid AI + action workflows.

For example, a GPT node can analyse an incoming email and decide to create a Jira task or a Slack alert depending on its content.

n8n is a great agent prototyping lab, although it is still limited in managing complex contexts or long agent memories.

Flowise, LangGraph, CrewAI 

These tools aim to comprehensively model AI agents: memory, role, tools, interactions between agents.

They sit at the intersection between orchestration and reasoning, an area that RPAs have never covered.

The era of ‘personal RPAs’: Intelligent automation for everyone

These tools do not yet replace enterprise RPA.

But they democratise intelligent automation:

• A consultant can create an agent that summarises client briefs and feeds them into Notion.
• A developer can automate their monitoring and trigger PRs on GitHub.
• A manager can receive Slack summaries generated automatically from PDF reports.

We are witnessing the birth of RPA accessible to individuals, tools that automate cognitive and contextual tasks where traditional RPA left off.
 

Agentic AI: Maturity and limitations for businesses

Despite their potential, these solutions are not yet fully ready for critical processes:

• Lack of governance, auditability and traceability, except for custom implementations.
• Difficulty in guaranteeing the predictability and security of AI actions.
• Risks related to hallucinations, misinterpretation of context and the non-determinism of LLMs.
• Few versioning, monitoring or rollback tools.

These limitations currently confine them to prototyping, personal automation, or non-critical scenarios.

But as with RPA in its early days, maturity will come: API standardisation, agent audits, ISO certifications, sandboxing of actions, etc.

Towards RPA x AI convergence

The established players in RPA are not standing still.

UiPath, Microsoft Power Automate and Automation Anywhere are already integrating LLMs to make their bots more ‘intelligent’.

The boundary is gradually blurring between:

• Traditional RPA (reliable but rigid)
• Cognitive RPA/AI (flexible but unpredictable)

The future lies in the fusion of these two worlds.

The Age of AI Agents: Why You Need to Prepare for It

We are entering an era where automation is no longer programmed, but trained and guided. 

Composio, n8n, Flowise and CrewAI are heralding this evolution: a new ecosystem of AI agents that are easy to create, interconnected and intelligent.

For CTOs, CDOs and CIOs, the message is clear: you need to start experimenting now, within controlled parameters, to understand the potential, limitations and future governance patterns of these technologies.
Because tomorrow, AI agents will not just be assistants, they will be autonomous digital collaborators, orchestrated by your systems.