Jan 16, 2025

Introduction As businesses prepare for 2025, industry experts are forecasting significant shifts in how companies will handle and utilise customer data . These changes span across multiple domains, from data infrastructure to artificial intelligence, with implications for businesses of all sizes. To understand these emerging trends, Amperity’s industry leaders shared their insights on what lies ahead. The Evolution of Data Infrastructure At the foundation of these changes lies the transformation of data infrastructure itself. In this space, significant consolidation appears to be on the horizon. Caleb Benningfield, Field CTO at Amperity, sees major changes coming to the Customer Data Platform (CDP) market. “There has been no clear winner and investors will want to see action and CDPs will begin to merge or be acquired,” he explains. Benningfield also predicts that companies will increasingly position themselves as alternatives to Salesforce Data Cloud while emphasising vendor independence. Additionally, he notes that “zero-copy” architectures will become essential for competitive CDPs. AI Transformation and Business Impact While data infrastructure provides the foundation, artificial intelligence is poised to be the driving force of innovation in 2025. The AI landscape is set for dramatic evolution, according to Joyce Gordon, Amperity’s Head of Generative AI . She emphasises that AI adoption will create a clear divide between companies that thrive and those that struggle. “These successful companies will make better decisions because their teams can easily access and understand data, deliver more personalised customer experiences using generative AI, and run more efficiently by using AI for tasks like drafting creative briefs and handling initial customer service responses,” Gordon explains. “Brands that aren’t adopting AI with a cohesive strategy will fall behind.” The Path to AI Success However, implementing AI successfully requires more than just adopting the technology. Gordon particularly emphasises the importance of proper AI implementation. “Companies will move beyond segmented AI-driven content, closer to one-to-one personalisation,” she says. “This shift is possible now because AI models are becoming smaller, cheaper, and more capable, and because companies are getting better at using them.” However, Gordon cautions that success requires clean, well-organised customer data as a foundation. Media Networks and Advertising Evolution As businesses grapple with these technological changes, the media and advertising landscape is undergoing its own transformation. Related Posts In the media and monetisation sphere, Peter Ibarra, Head of Media and Adtech Solutions at Amperity, predicts significant changes in retail media networks (RMNs). “The explosion of retail media networks over the past few years means we’re close to a tipping point,” he notes. Ibarra explains that success will require these networks to mature their offerings and provide truly differentiated targeting and measurement capabilities. The Future of Digital Advertising This evolution in media networks is closely tied to broader changes in digital advertising. Despite Google’s extension of third-party cookies, Ibarra believes advertisers won’t slow their investments in alternative technologies. “Brands will need to maximise the quality of their first-party signals as opposed to relying on the volume of their data,” he states. He also predicts that television advertising budgets will continue shifting from traditional linear TV to connected TV (CTV), with programmatic exchanges emerging as the winners. Transforming Customer Data Management These changes in advertising and media naturally lead to questions about how businesses will manage their customer data going forward. Looking at the broader customer data landscape, Amperity CTO and co-founder Derek Slager sees fundamental changes ahead. “The CDP category will continue to fragment, with vendors more explicitly aligning their positioning to their strengths rather than claiming to solve things entirely,” he predicts. Slager believes that rather than seeking single-platform solutions, companies will increasingly adopt multiple specialised tools to address their customer data challenges. Analytics and Real-Time Capabilities This transformation in data management will be accompanied by significant changes in how businesses analyse and act on their data. Slager is particularly bullish on AI’s role in transforming analytics . “Dashboards are dead,” he declares. “Generative AI powered tools offering the ability to answer the questions that matter on-the-fly will be the new surface for analytics and decision making.” Slager also predicts a resurgence in real-time capabilities across the entire data stack , driven by competition in the Cloud Data Warehouse market. The Rise of Low-Code Solutions Looking to the future, perhaps the most transformative change will come from democratising access to these powerful technologies. Slager foresees the emergence of a new generation of AI-powered low-code and no-code tools that will quickly compete for enterprise use cases. This development could dramatically change how businesses approach their data infrastructure and analytics needs in the coming year, making sophisticated data operations accessible to a broader range of organisations and users. 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