Which Team Should Be Responsible for Integrating AI into Your Product?

Introduction

In today's rapidly evolving marketing technology landscape, AI integration has become a critical component of effective customer experience strategies. Joyce Gordon, Head of AI at Amperity, brings her extensive expertise in AI-driven customer identity resolution to address one of the most pressing questions facing organizations: which team should take ownership of AI implementation? With her background helping Fortune 500 brands solve data fragmentation challenges, Gordon offers valuable insights into the collaborative approach needed to successfully leverage AI for personalized marketing initiatives.

Cross-Functional Collaboration for AI Integration

When it comes to integrating AI into products and marketing systems, Gordon emphasizes that idea generation should be democratized across the organization. "One thing that's super important is the ideas for how to integrate AI and the use cases should be sourced from your entire company," she explains. This inclusive approach ensures that AI implementations address real business needs across departments and leverage diverse perspectives. However, Gordon maintains that the technical implementation work ultimately falls to product and engineering teams who possess the specialized expertise required for successful integration.

The Evolving Role of Business Teams

While technical teams may lead implementation, the traditional divide between business and technical roles is rapidly narrowing. With the emergence of natural language interfaces and low-code AI tools, marketing and business teams now have unprecedented capabilities to participate in AI development. Business teams are increasingly positioned to identify use cases, conduct testing, and drive the strategic direction of AI initiatives without requiring deep technical expertise. This shift represents a significant opportunity for marketing professionals to take a more active role in shaping AI-powered customer experiences.

Technical Infrastructure Remains an Engineering Domain

Despite the democratization of AI tools, Gordon clarifies an important distinction in responsibilities: "I think setting up the underlying systems and hooking up the LLMs throughout your business and really developing the infrastructure—that will still live with the product and engineering teams." This perspective highlights that while business users can increasingly leverage AI capabilities, the foundational architecture that enables these capabilities remains the domain of technical specialists. Organizations must recognize this division of responsibilities to create effective AI governance models.

Building a Unified Data Foundation

A critical insight from Gordon's expertise at Amperity is the importance of having a unified customer data foundation before attempting sophisticated AI personalization. Without consolidated, high-quality customer data, even the most advanced AI implementations will struggle to deliver meaningful results. Organizations should prioritize resolving data fragmentation issues across their marketing technology stack to create the necessary foundation for AI-powered personalization. This approach ensures that AI systems have access to comprehensive customer insights that can drive truly personalized experiences.

Key Takeaways

The most effective AI integration strategies embrace a hybrid approach where business teams identify opportunities and use cases while technical teams build and maintain the underlying infrastructure. As AI tools become more accessible through natural language interfaces, marketing professionals have greater opportunity to directly shape AI implementations. However, successful AI personalization ultimately depends on having a unified data foundation that provides comprehensive customer insights. By fostering collaboration between technical and business teams while maintaining clear responsibility boundaries, organizations can maximize the transformative potential of AI for creating exceptional customer experiences.