Industry executives and experts share their predictions for 2026. Read them in this 18th annual VMblog.com series exclusive.
By Derek Slager, co-founder and CTO, Amperity
In 2025, enterprises continue to invest heavily in artificial intelligence, yet many still struggle to see meaningful returns. The gap lies not in technology, but in how data is managed and activated to fuel it. For example, in the travel sector, roughly 80% of brands report using AI in some capacity, but only 12.5% feel confident they can scale it across the business.
The retail industry is finding similar trepidation. According to a recent report, 97% of retail executives plan to maintain or increase their AI investment in the coming year, though only around 11% feel fully ready for scaled deployment.
Looking ahead to 2026 and beyond, the direction is clear: It’s not more AI tools that will unlock growth, but smarter use of data. The next wave of gains will come from moving fragmented, static data lakes to unified, intelligent data systems. The modern Customer Data Platform (CDP) is evolving beyond a repository of records into a system of intelligence, serving as the nervous system that drives adaptive, agentic AI and delivers significantly better business results.
To compete in an AI-driven enterprise landscape, data architecture must evolve in tandem with the technology itself. The following predictions illustrate how CDPs will move from static infrastructure to intelligent, interoperable systems that harness AI at scale.
1. Data Platforms Shift to Engines of Intelligence
Originally, CDPs were built to integrate data silos, unify customer records, and provide single-view dashboards. In other words: record, store, visualize. However, in 2026 and beyond, they will take on a more dynamic role, embedding AI agents that analyze unified data, generate insights, activate real-time decisions, and then review the results to recommend next best actions in a continuous, iterative cycle. That shift transforms a passive database into an active intelligence engine – one designed to sense customer intent, surface opportunities, and drive actions across marketing, operations, and service.
2. Agentic AI at the Core of Intelligent Customer Platforms
Building on this intelligence layer, agentic AI brings together autonomous systems that operate independently within brand-defined goals. When connected to a CDP as the unified intelligence hub, it turns personalization into a continuous, self-improving process.
Customer experiences will no longer be built once and reused. Instead, they will adapt in real time as people interact. Marketing technology will shift from isolated tools into a network of interoperable, connected AI agents. For example, the AI agents perform specialized functions-one monitors customer behavior, another optimizes offers, and a third adjusts pricing-all drawing from the same underlying customer data. The modern CDP is the central intelligence system that trains, validates, and manages these agents.
3. Creative and Data Workflows Unite for a Unified Marketing Layer
As agentic AI transforms the way decisions are made, it will also redefine how marketing teams operate. Today, creative development still sits in a separate workflow from data analysis and audience strategy, creating two functions that rely on each other but operate on disconnected timelines. Those steps will merge into a single, continuous environment.
AI systems will generate content based on live customer context, drawing from unified profiles, behavioral signals, and intent data to shape each step of the process. Instead of exporting segments into creative tools or waiting for performance data to guide revisions, brands will work within an integrated environment where insights and execution inform one another instantly.
This convergence will accelerate go-to-market cycles and help teams deliver campaigns that are more consistent and relevant. As a result, the marketing stack becomes lighter, more connected, and more focused on driving outcomes.
4. A Shift from Integration to Orchestration and Interoperability
Integration used to be the main goal of CDPs, connecting old systems, exporting/importing data, and enabling dashboards. Now, the focus is on interoperability, where systems work together smoothly without friction, duplication, or delay.
Future CDPs will operate as intelligent orchestration layers where AI agents handle the work that once required separate marketing automation tools and business intelligence platforms. Instead of pushing data into downstream systems, these agents will interpret unified customer data, trigger personalized actions in the moment, evaluate outcomes, and adjust decisions on their own. In this model, insights flow continuously, actions adapt in real time, and the lineage of every decision remains intact – all without relying on the legacy tools of the previous era.
5. Composable CDPs: Connecting Data Without Duplication
The next evolution builds on orchestration. Today, brands are seeking greater flexibility and efficiency, moving away from redundant or fragmented data processes. The next generation of CDPs will be composable and use a “zero-copy” approach. Rather than copying data into separate silos, these platforms will connect directly to lakehouse and cloud systems, using existing storage, computing power, and models without creating duplicates.
For example, a retailer could run a customer segmentation analysis directly on its cloud data warehouse, leveraging real-time purchase and browsing data without exporting or duplicating it. This architecture reduces cost, improves governance, and accelerates innovation. Brands maintain full control, integrate with existing systems, and grow their data intelligence without replicating the data chaos of the past.
6. Building Loyalty with Trusted Data
Perhaps the most significant shift in the AI era is how trust is shaping business strategy. Brands will differentiate themselves not just through speed or personalization, but through transparency and clear, explainable AI decisions.
CDPs will surface not only “what we know about a customer,” but “how we know it, when we last updated it, and what we will do with it.” Rule-based compliance evolves into brand architecture, making reliable data a key factor in customer loyalty, rather than just a means to meet regulations.
Shaping the Future with Intelligent, Trusted Data Systems
As 2026 approaches, smart data systems, AI accountability, and agent-driven environments will reshape how companies are organized. CDPs will move beyond being stand-alone tools and become the intelligence layer for networks of AI agents, all sharing a common customer base. Meanwhile, data infrastructure and IT systems will come together, making it possible to coordinate analytics, automation, and decisions in real time.
The focus for the future is not just on adding more AI, but on using it more wisely, with intelligence, integrity, and valuable insights at the core.
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ABOUT THE AUTHOR
Derek co-founded Amperity to create a tool that would give marketers and analysts access to accurate, consistent and comprehensive customer data. As CTO, he leads the company’s product, engineering, operations and information security teams to deliver on Amperity’s mission of helping people use data to serve customers. Prior to Amperity, Derek was on the founding team at Appature and held engineering leadership positions at various business and consumer-facing startups, focusing on large-scale distributed systems and security.
