The great reversal: How incumbent brands beat digital natives at their own game
Implementing context intelligence across siloed systems provides the trusted, real-time data foundation needed to power accurate AI models
By Manish Sood, CEO & Founder, Reltio
The past two decades have taught us a simple lesson: startups win when incumbents are unable to make sense of the assets they already have. After the Great Recession, thousands of digital-native startups surged ahead as consumers began drifting towards a frictionless “Amazon-like” experience, rather than prioritising brand recognition. Startups had a key factor in their favour: they were not weighed down by decades of systems, processes and data debt. Meanwhile, the companies they sought to disrupt were struggling to move their vast troves of records from paper to digital.
Established companies did have something far more valuable, of course — deep customer relationships, industry knowledge and vast amounts of historical data — but they couldn’t use any of it effectively. Their data was scattered across old systems, incompatible applications and organisational silos. Insights that could have powered innovation sat trapped in disconnected databases.
Why incumbents fell behind — and why they’re catching up now
Startups promised disruption because they were free of legacy baggage. They didn’t inherit 30-year-old mainframes, dozens of customer relation management (CRM) systems, or business units that all built their own tech stacks. They could ship quickly and scale with cloud-native systems.
Incumbents, even those with centuries of history, were stuck with having to maintain an ever-growing tangle of technology. Every new system added more fragmentation. Decisions were made on partial views of the customer. AI models couldn’t be trained on complete histories. Innovation stalled.
The real moat: historical data made usable
A startup can build a modern interface, but it can’t recreate decades of customer behaviour, transactions, claims, loyalty patterns or risk profiles. These histories contain the kind of intelligence that makes AI far more accurate and useful. But incumbents could only use this data once it was unified and accessible across the enterprise.
CarMax is a clear example. Once it had connected its dealership systems, online platforms, service data and customer interactions, it was not only a match for digital natives, but became the largest used car retailer in the US. The company, born in the brick-and-mortar era, personalised every moment of the customer journey with the depth of insight only a long-time market leader can possess.
This same shift is happening across retail, insurance, healthcare and financial services. The formula is simple: unify the data, activate the history, create a context layer, and apply it with modern tools and AI.
Why context intelligence matters now
Unifying data is only the first step. What gives incumbents an edge in the age of AI is something broader: context intelligence.
Context intelligence is the ability to understand every entity — customer, product, provider, location, supplier — in relation to all the interactions, events and signals around it. It connects the dots across systems and moments in time to enable companies to act with precision instead of guesswork.
For large enterprises, context intelligence is important because:
AI needs context to work well. Models trained on incomplete or inconsistent data make poor decisions. Rich, connected histories dramatically improve accuracy.
Real-time operations depend on a shared understanding. Sales, service, marketing and digital channels can’t deliver seamless experiences unless they’re working from the same, current picture.
Regulated industries can’t rely on uncertain shortcuts based on probabilities. Banks, insurers, and healthcare organisations need decisions rooted in trusted, traceable data.
It levels the playing field against digital natives. Startups may move quickly, but incumbents can train models on deeper and more relevant context — a powerful competitive advantage.
Context intelligence turns raw data from all potential sources into something enterprises can actually use: knowledge about what matters, why it matters and what should happen next. As shown in Figure 2, a system of this kind creates context-rich, unified data and sends the same trusted information to all potential consumers.
The winning pattern
Startups still move fast. But incumbents are beginning to move faster at a bigger scale with far better inputs. Once they confront data fragmentation and activate context intelligence, they combine the scale, trust and history of a mature enterprise with the speed and precision of a digital native.
The story of disruption isn’t ending — it’s evolving. The companies winning now aren’t the ones with the cleanest slate. They’re the ones that finally learned how to use what they’ve had all along.
See how leading enterprises are unifying trusted data to reclaim advantage — explore all Reltio resources.