Change Management in the AI Era: Elevating Product Data from Cost Center to Competitive Advantage

After speaking at both Akeneo Unlock and Salsify DSS last week, one theme consistently emerged in my conversations with digital commerce leaders: the critical need for effective change management as organizations integrate AI into their product data operations. What’s truly remarkable is how deeply this topic resonates across industries and company sizes. The message is clear: technology alone isn’t enough—how we lead our teams through transformation determines success.

The Product Data Paradigm Shift

For too long, product data management has been viewed as a necessary but unglamorous cost center—a back-office function focused on maintenance rather than innovation. This outdated perspective is rapidly changing as forward-thinking organizations recognize that exceptional product information is a powerful competitive differentiator in today’s digital-first marketplace.

The integration of AI into PIM, PXM, and DAM systems offers an unprecedented opportunity to reframe how the entire organization perceives product data teams. When properly implemented and supported, AI enables these teams to transition from being perceived as operational cost centers doing commoditized work to strategic profit centers driving measurable business growth.

Consider the impact of AI-enhanced product content: improved search rankings, increased conversion rates, reduced return rates, and accelerated time-to-market. These aren’t merely operational improvements—they directly impact revenue and customer experience. The question isn’t whether you can afford to invest in AI-powered product data capabilities, but whether you can afford not to.

Change Management Must Start at the Top

Successful transformation in this domain requires more than purchasing new AI solutions or hiring data scientists. It demands intentional change management led from the executive level. As I shared with conference attendees last week, organizations that attempt to implement AI without executive championship inevitably struggle with adoption, alignment, and measurable results.

Effective change management begins with leadership that:

1. Champions a Clear Vision: Executives must articulate how AI-enhanced product information drives strategic business goals and competitive differentiation. This means communicating not just what will change, but why it matters to the organization’s future success.
2. Reframes the Value Proposition: Leadership needs to explicitly position product data teams as drivers of revenue and customer experience, not as cost centers. This shift in perception must be reinforced through messaging, resource allocation, and performance metrics.
3. Allocates Meaningful Resources: True championship goes beyond verbal support. It requires investment in technology, dedicated implementation time, appropriate staffing, and ongoing training to build new capabilities.
4. Creates Cross-Functional Alignment: Product data touches nearly every aspect of commerce operations. Executive leaders must foster collaboration across departments—breaking down silos between marketing, merchandising, IT, and operations to ensure unified efforts.
5. Models Adaptability: Leaders who demonstrate openness to experimentation, comfort with iteration, and willingness to learn send powerful signals throughout the organization about embracing change.

Building a Profit Center Mindset

The transformation from cost center to profit center requires not just new technology but new thinking. Teams accustomed to being measured on efficiency metrics must shift toward impact metrics that demonstrate their contribution to revenue and customer experience.

This means establishing clear KPIs that connect product data quality to business outcomes: conversion rate improvements, search result placement, customer satisfaction scores, and market share growth. When product data teams can point to their direct impact on these metrics, their perceived value within the organization fundamentally changes.

AI adoption accelerates this shift by allowing teams to focus less on manual data enrichment and more on strategic initiatives that drive competitive advantage. The most successful organizations I’ve worked with have redefined product data roles to emphasize analysis, strategy, and continuous improvement rather than repetitive data entry.

The Competitive Imperative

As I discussed with digital leaders last week, organizations that successfully navigate this change gain substantial advantages over competitors. They move faster, create more compelling customer experiences, and make better data-driven decisions. Importantly, they also attract and retain top talent who want to work on innovative, strategically valued teams.

The contrast between organizations embracing this change and those resisting it grows more pronounced every day. In one telling example shared at last week’s conference, a retailer implementing AI-powered product content generation reduced time-to-market by 60% while simultaneously improving content quality scores by 40%—creating a competitive advantage that would be nearly impossible to match using traditional approaches.

Next Steps on Your Transformation Journey

Leading change of this magnitude requires both vision and practical guidance. Whether you’re just beginning to explore AI’s potential for your product data operations or are already implementing solutions, thoughtful change management remains the critical success factor.

Want a comprehensive framework for leading AI-driven transformation in your organization? My new ebook “Digital Commerce Reimagined” provides a detailed roadmap for elevating product data from cost center to competitive differentiator, with specific strategies for executive leaders.

Download the complete ebook here to access practical guidance on change management, talent development, implementation planning, and measuring success in the AI era.