Agentic AI Rises in Mexico Amid Data, Integration Hurdles

Agentic AI, or AI systems capable of acting and making decisions autonomously, is emerging as a transformative technology for companies in Mexico. However, its effective implementation faces significant barriers related to data quality, systems integration, and the need for a cultural shift in organizations, opening a strategic field of action for the IT channel.

The promise of Agentic AI is to move from simple task automation to the execution of autonomous, adaptive, and scalable workflows. However, its success depends on a solid foundation. “Agentic AI has significant potential, but it does not work in a vacuum: it requires quality data, deep integration with applications, and clear processes,” says Paulina Treviño, Director of Solution Engineering at Salesforce.

The interest in Agentic AI within the Mexican business sector stems from its ability to optimize operations at a level beyond that of traditional AI. While Generative AI can create content or analyze information to offer recommendations, agentic AI acts on those recommendations, reports MBN. For example, it can not only detect a potential disruption in the supply chain but also autonomously execute actions to mitigate it, such as reallocating inventory or generating purchase orders to alternative suppliers.

“Much as software-as-a-service (SaaS) started horizontal and then went vertical, we are seeing a similar dynamic playing out in AI: we started with ChatGPT, but are now seeing a proliferation of industry-specific tools such as agents,” write Patrick and John Collison, Co-Founders, Stripe, in their 2024 annual letter.

This capacity for autonomous action presents high-value opportunities across multiple sectors. In the retail industry, it can manage inventory in real time, while it can execute trades based on market analysis in the financial sector and proactively monitor and optimize resource consumption in the sustainability field, says Treviño. The application of agentic AI for sustainability is a promising area, as these systems can continuously analyze the environmental impact of operations and adjust processes to reduce the carbon footprint, generating accurate reports that facilitate compliance with environmental, social, and governance (ESG) objectives.

“AI delivers the most impactful value when it works seamlessly across an entire business,” writes Greg Pavlik, Executive Vice President of AI and Data Management Services, OCI, in a press release. “IBM and Oracle have been collaborating to drive customer success for decades, and our expanded partnership will provide customers new ways to help transform their businesses with AI.”

Despite its potential, the implementation of agentic AI in Mexico faces considerable technical and strategic challenges. Salesforce reveals that 93% of IT leaders who already use AI agents believe that data integration is key. On average, organizations use nearly 900 different applications, which creates information silos that limit the ability of agents to operate effectively. This is especially important considering that these agents are only as good as the data that feeds them. If the data is fragmented or of low quality, performance and reliability are compromised.

The successful deployment of AI agents depends on a robust foundational infrastructure, says Hospitality Investor. This includes unified data systems that ensure consistent and accurate information across platforms, as well as flexible APIs that allow seamless integration with existing tools and services. Equally important are strong security and compliance frameworks to protect sensitive data and ensure adherence to regulatory standards. Finally, organizations must develop a clear strategy for human-AI collaboration, defining how agents will augment human roles and ensuring workflows are designed to support effective interaction between people and intelligent systems.