How An Abbvie AI Director Solves Integration Woes By Embedding AI Into Core Functions From The Ground Up

*The views expressed in this article belong to Sergio Gutiérrez-Montero and do not necessarily reflect the official policy of any organization.

The biggest problem in enterprise AI isn’t the technology. It’s what companies are doing with it. Companies are investing in pilots, isolated tools, and chatbots, yet most are failing to generate meaningful ROI. In fact, up to 95% of organizations get zero return on their GenAI investments. The reason is simple: AI is not being truly embedded into core business operations.

For an expert's perspective, we spoke with Sergio Gutiérrez-Montero, Director of AI Strategy & Implementation at pharmaceutical manufacturer, AbbVie. Drawing on over 20 years of experience leading digital transformation at firms like McKinsey & Company, where he helped launch a projected $300M+ digital care concept for a major cancer center, Gutiérrez-Montero offered a frank perspective on navigating the hype. Instead of a plug-and-play approach, organizations must treat AI integration as a fundamental design challenge, he explained.

“We’re in this stage where we build a chatbot, and we are happy. But most of the power, the value unlocked by AI, is going to come from embedding it into your workflows. That's a design problem in itself. You can’t just switch one box in an existing process and make it automatic. You have to reinvent the process to be truly AI-native,” Gutiérrez-Montero said.

Fragmented systems and poor data quality can make it difficult to build effective AI, Gutiérrez-Montero admitted. But he also reframed this problem as a strategic opportunity. For him, the promise of AI is a powerful "forcing mechanism" that justifies cleaning up years of tech debt. Most of that work includes migrating to the cloud, building a middleware layer, and establishing observability to track value. But beyond the technical requirements, transformation depends on the human element.

• The trust bottleneck: Without trust, AI fails to deliver on its primary promise of creating leverage and enterprise-wide scale, Gutiérrez-Montero said. "You have to generate trust among your employees to use AI. If an employee needs to check the outputs of an AI system every time because they don't trust it, you are creating a bottleneck and not leveraging the scale of AI."