Adapting to Change: Why Incumbents Thrive Beyond Just AI Technology
In today’s rapidly evolving technology landscape, there is a widespread narrative that incumbent companies are losing ground to AI-native startups simply because these startups built their products with the latest AI technology from the outset. The assumption often goes like this: incumbents are retrofitting outdated products with AI features—like chatbots—while startups innovate fresh, AI-first solutions, inevitably causing incumbents’ decline.
However, this view oversimplifies a much more complex dynamic. Many incumbents are not only surviving but thriving in the AI era. The real advantage doesn’t lie merely in the novelty of technology stacks but in how well companies understand and adapt to their customers’ evolving needs. The age of a software product or its underlying technology is often less crucial than its relevance to the shifting problems customers face.
Learning from Past Technology Waves
Having observed the transitions from web to mobile, then cloud computing, and now AI, it’s clear that success comes from more than just adopting new technology. Across these waves, some incumbents thrived while others decayed; some startups redefined entire categories, and some were overtaken by established players.
What differentiates winners is often their close, continuous relationship with customers. Those who thrive stay attuned to the subtle ways the problems their customers hired them to solve evolve over time. They innovate not by chasing every new feature but by addressing the core, shifting challenges their customers face.
A Practical Example: Evolving Customer Problems in SaaS Accounting Software
Consider a cloud-based SaaS company specializing in small-business accounting software. Initially, it gained a strong market position by enabling business owners to track transactions, send invoices, and close their books accurately—tasks that were crucial at the time.
But over time, customers’ needs shifted. While the software ensured accuracy, it did little to improve efficiency. Business owners still spent hours on repetitive, manual tasks instead of focusing on strategic financial activities. At this juncture, the incumbent has two choices: dismiss efficiency as outside their domain or embrace it as a new problem to solve.
Companies that ignore this shift don’t face a single disruptive event. Instead, startups incrementally build complementary solutions—automated revenue recognition, forecasting tools, and more—that gradually chip away at the incumbent’s market share. Customers eventually question why they continue paying for software that doesn’t solve today’s problems.
The Playbook for Staying Ahead
Focus on the evolving problem, not just features. It’s common for product teams to optimize roadmaps or sales funnels without regularly reevaluating whether the original customer problem has changed. Understanding the history and trajectory of a customer’s problem is vital. Leaders should ask: How did the problem start? How has our solution changed it? What future changes might technology or market trends bring?
Instead of asking customers what new features to build—a question that often leads to unclear or unhelpful answers—companies should engage customers with deeper questions:
- Why did you adopt our product initially, and how has that problem evolved?
- How has our product changed your experience of that problem?
- What challenges are we overlooking?
- Which recurring tasks frustrate your team most?
- What will your team and technology look like in five years, and why?
Consistently asking these questions across conversations helps companies detect emerging needs and pivot their product strategies accordingly. It’s crucial to distinguish a feature pipeline—a list of incremental improvements—from a strategic approach that addresses fundamental customer problems.
Tactical Steps for Product Innovation
- Review recent renewal and churn calls for language indicating changing needs, such as “still” versus “but now.” The “but now” often signals emerging pain points.
- Consult customer success teams to identify requests that are ignored because “it’s not our focus.” Patterns here can reveal unmet needs.
- Regularly join customer calls to listen firsthand to how clients describe their problems and frustrations.
- Spend time with advisory customers who represent your ideal profile to deeply understand the evolution of their challenges.
Build technology with adaptability in mind. If product extensions require tearing apart the core system, innovation slows. Modular architectures enable faster integration of adjacent capabilities—like automation or forecasting—helping incumbents stay competitive and retain customers.
Maintain an ongoing commitment to product strategy. Even after hiring product leaders, founders and executives should remain students of the customer’s evolving needs. This vigilance helps challenge assumptions and guides long-term innovation.
Conclusion: Avoiding Complacency in the AI Era
By focusing on evolving customer problems, building adaptable technologies, and maintaining strategic oversight, companies can remain relevant and innovative through every technological shift. Complacency is a competitor’s opportunity—when incumbents grow overconfident, startups asking the right questions and solving today’s problems can swiftly gain ground.
In today’s AI-driven landscape, the line between startup and incumbent blurs quickly, and staying ahead demands a relentless focus on customer needs rather than technology alone.
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