AI is one of the defining technology priorities for B2B organizations. Marketing and sales leaders expect it to accelerate decision-making, improve buyer experiences, and drive greater operational efficiency. For IT leaders, the challenge is creating the connected data foundation that allows those technologies to deliver on their promise.
That foundation is increasingly important because modern B2B engagement depends on customer, account, and buying group data moving effortlessly across systems, teams, and applications. But many organizations are still trying to modernize buyer experiences while relying on fragmented data architecture that was never designed to support real-time coordination.
In a 2026 Demand Gen Report, 96% of marketers said they already use AI in their roles. Yet Adobe’s 2026 AI and Digital Trends Report found that only 44% of organizations believe their data quality and accessibility are adequate for AI. Together, those findings highlight a growing disconnect: organizations are embracing AI faster than they’re modernizing the data foundation that AI depends on.
The architecture gap between customer expectations and enterprise reality
Compounding the challenge, B2B buying has changed.
Today’s buying journeys involve larger buying groups, more digital interactions, and more channels than ever before. Buyers expect organizations to recognize their interests, understand where they are in the journey, and respond with relevant information, often before they ever speak with sales.
Meeting those expectations places new demands on enterprise architecture. Customer, account, and buying group data now flows through customer relationship management (CRM) platforms, marketing systems, analytics environments, cloud applications, and data warehouses. As organizations continue adding technologies, integration gaps emerge, duplicate records accumulate, and manual processes increase.
Disconnected systems create disconnected decisions
Fragmented data is both an operational inconvenience for IT organizations and a business constraint.
Marketing and sales teams often work from different versions of customer and account information. Analytics platforms may tell one story while CRM and campaign systems tell another. Customer context is incomplete, making it difficult to coordinate outreach, prioritize accounts, or support AI-driven decision-making with confidence.
The challenge only grows as organizations collect more information. According to a 2026 B2B Content and Marketing Trends Report, “91% of B2B marketers collect first-party data, but half admit their strategy is still in the exploratory (19%) or developing (31%) stages.” Yet more data doesn’t automatically create better decisions. Connected data does.
Start by adapting what you already have
The next step isn’t replacing every platform. It’s improving how existing platforms work together. Over time, these incremental improvements build a stronger architecture to support AI readiness, operational efficiency, and faster decision-making without disrupting existing investments.
A connected architecture means that customer and account information are visible across teams and systems. By unifying your architecture, your systems operate as a shared foundation for intelligence, automation, and execution. This reduces unnecessary data movement, simplifies operations, and makes trusted information easier to access.
Building the foundation for the next generation of B2B engagement
As AI, automation, and B2B buyer expectations evolve, competitive advantage will depend on how effectively organizations connect the systems and data they already have.
Adobe Experience Platform creates a connected, unified data foundation. Amazon Web Services (AWS) provides the cloud infrastructure, data services, and AI capabilities to process that information at scale. Together, they help organizations modernize legacy data architecture and act on insights faster.
Learn how Adobe Experience Platform on AWS helps organizations modernize fragmented customer data and engagement workflows, explore the guide Real-time B2B engagement requires connected, unified data architecture.
