Key Takeaways

• OutSystems CEO Paulo Rosado calls the AI revolution oversold
• The company just launched its new Agentic AI platform
• Agentic AI offers an agent marketplace and Context Protocol for integrations
• Early adopters report major efficiency gains with Agentic AI
• Rosado urges balanced adoption tied to real business outcomes

Why Some Call the AI Revolution Oversold

Many tech leaders praise AI for its promise. However, OutSystems CEO Paulo Rosado feels the hype is overblown. He says most marketing talks of AI lack solid results. In fact, he believes the industry talks more than it delivers. Thus, companies chase flashy features rather than solving real problems.

Rosado warns that firms rush into AI without clear goals. They buy tools, but they do not track outcomes. Consequently, budgets swell and projects stall. In his view, this approach hurts both users and the reputation of AI itself.

At the same time, OutSystems is stepping forward with its own solution. They want to show practical AI that delivers real gains. They call it Agentic AI, a platform designed for ease and scale.

Inside the Agentic AI Platform

OutSystems built Agentic AI to bridge the gap between hype and value. It packs two standout features. First, an agent marketplace. This lets teams pick ready-made agents for tasks like customer support or data analysis. Second, the Model Context Protocol. This tool ensures AI models connect smoothly with existing systems and data.

By offering these tools, Agentic AI aims to speed up real deployments. Moreover, it lowers the technical barriers to entry. Teams no longer need deep AI expertise to launch new applications. Instead, they can focus on solving business needs.

Key Features of the Agent Marketplace

• Prebuilt agents for common tasks
• Easy customization with no code changes
• A library that grows over time
• Community contributions for shared improvements

How the Model Context Protocol Works

• Defines clear rules for data exchange
• Ensures data privacy and security
• Maintains consistent performance as use scales
• Supports multiple AI models in one framework

Early Wins and Real Value

Several early adopters have already tested Agentic AI. They report faster project timelines and lower costs. One financial firm slashed its loan processing time by half. Another retailer boosted online sales by automating product recommendations. In both cases, teams tied results directly to the platform’s tools.

Critically, these teams started small. They picked one business problem to solve. Then, they measured impact before adding more agents. This discipline prevented wasted effort and kept costs in check. It also proved Rosado’s point. When AI moves from hype to real use, people see the true value.

Moreover, users say the agent marketplace saved weeks of setup time. They simply chose an agent, tweaked a few settings, and launched. Likewise, the Protocol ensured their data stayed secure and consistent. As a result, they avoided the common pitfalls of AI projects.

A Balanced Path to AI Adoption

Rosado advocates a measured approach. He says companies should ask three questions first: What problem do we want to solve? How will we measure success? Can we scale this solution? By answering these, teams build a roadmap for AI that delivers clear benefits.

He also stresses the importance of collaboration. IT teams, business leaders, and end users must align on goals. In addition, they should revisit those goals regularly. This avoids drifting into projects that feel cool but add no value.

Furthermore, Rosado sees education as vital. Many employees still fear AI or mistrust its results. Therefore, he encourages leaders to train their staff. With proper guidance, teams can use AI safely and effectively.

In short, the message is clear. AI should serve real needs. If it does not, it remains just buzz.

Key Steps for Balanced Adoption

• Define clear business objectives
• Start with small, focused pilots
• Measure outcomes against set goals
• Scale only after proven success
• Invest in team training and support

Practical Tips to Avoid the Hype Trap

First, document every AI project from day one. Second, involve stakeholders across the company. Third, choose tools that integrate smoothly with existing systems. Fourth, prioritize data security and ethics. Finally, report results in plain language so everyone understands the impact.

Looking Ahead for Agentic AI

OutSystems plans to expand its agent marketplace steadily. In addition, they will update the Model Context Protocol to cover more use cases. They invite partners to contribute new agents and share best practices. As more companies join, the community will grow stronger.

Rosado hopes that this approach will reset the AI conversation. He wants conversations to focus on real outcomes, not flashy demos. He believes Agentic AI can lead the way by proving that balanced, goal-driven AI creates true business value.

Frequently Asked Questions

What makes Agentic AI different from other AI tools?

Agentic AI combines a ready-to-go agent marketplace with a robust Context Protocol. This lets teams deploy and scale AI quickly without complex coding. It focuses on practical business use rather than experimental features.

How can small businesses benefit from Agentic AI?

Small businesses can start with a single agent to solve one problem, such as customer support automation. They can track results, refine their approach, and expand only when they see clear gains. This keeps costs low and outcomes high.

Is specialized AI expertise needed to use Agentic AI?

No. Agentic AI’s design minimizes the need for deep AI knowledge. The marketplace offers prebuilt agents you can customize with simple settings. The Protocol takes care of data handling behind the scenes.

How does the Model Context Protocol ensure data security?

The Protocol defines strict rules for how AI models access and share data. It enforces encryption and access controls. In addition, it logs every transaction for audit and compliance. This way, your data remains safe at scale.