In the race to dominate the commerce landscape, many businesses are making a critical mistake. They are trying to pour investment into a vessel full of holes. While the allure of agentic commerce and AI-driven personalization is strong, these advanced capabilities cannot operate effectively atop fragmented data and brittle legacy architectures. This is why a commerce stack review cannot wait. The technical debt you tolerate today will prevent you from adopting the agentic tools of tomorrow
The hidden cost of making it work
Many businesses today are trapped in a cycle of “duct-tape” digital transformation. They face a recognizable tension between the desire for rapid innovation and the heavy weight of technical debt. I frequently see brands struggling with four major pitfalls that drain their resources.
- Legacy technologies: Stacks that were cutting-edge years ago now act as anchors. They prevent brands from scaling or adopting modern, modular architectures that the current market demands. This inertia comes with an invisible tax on productivity: developers spend up to 42% of their time dealing with technical debt rather than new feature development.
- The implementation gap: High-velocity technology adoption often creates a divide between digital tools and the people who use them. When companies rush into deployment without aligning the software to their business processes or integrating it with the rest of their tech stack, they inadvertently create manual bottlenecks and data silos. Instead of accelerating growth, these disconnected systems become an operational burden that requires constant manual intervention to bridge the gaps.
- Data and AI readiness: Brands want to enable AI-ready commerce platforms, but they lack the clean, governed, and accessible data required to power these models. You cannot build a market-leading AI shopping assistant on a foundation of messy, siloed information. The market sentiment is absolute on this: 96% of IT and business leaders agree that the success of AI agents depends heavily on seamless, debt-free data integration. Without it, the risk of failure is stark. Gartner predicts that through 2026, organizations will abandon 60% of AI projects unsupported by AI-ready data
- Process and governance friction: Often, it is not the technology itself that fails. Instead, siloed workflows and unclear governance and ownership prevent effective technology delivery and operational excellence.
The result of these issues is that you end up over-customizing and investing in solutions that create additional technical debt. This increases your total cost of ownership while significantly decreasing your agility.
A structured framework for resolution
To stop optimizing for the past and start building for the future, you need more than a quick fix. You need a methodical diagnostic and health check that uncovers both technical and non-technical domains. It isn’t an overnight process, but it typically takes less than a month to fully assess the landscape and identify where the friction actually lives. The point isn’t to just generate a list of problems. It’s about building a prioritized roadmap for the way forward. I’ve found that focusing on four critical pillars is the most effective way to ensure the work actually sticks.
1. Architecture review
It is important to analyze the backend, third-party extensions, and system integrations against industry best practices. This includes looking for ways to simplify the tech stack. A common finding is that clients can better leverage “best of breed” applications or out-of-the-box capabilities to streamline their architecture to lower costs. This may involve leveraging AI tech.
2.AI Readiness
While businesses are moving fast to adopt AI, the existing tech stack often ends up being the very thing holding them back. It’s worth taking a hard look at whether there are fundamental gaps in architecture or data readiness that might stall an implementation before it even starts. With the market currently flooded with new tools, the challenge is shifting from finding an AI option to picking the right one. It’s less about following the hype and more about evaluating platform decisions to ensure they actually fit the long-term strategy
3. Strategic and solution fit
An evaluation of the current tech stack against long-term business goals is important to establish. Determining if systems are designed to communicate effectively or if they are creating a fragmented experience for customers is important to assess.
4. Management and governance review
A review of product management processes, quality assurance standards, and team structures is often overlooked but can be critical to the smooth operation of commerce technology modernization. By identifying gaps in governance, you can ensure that once the technical issues are resolved, you are actually equipped to maintain that desired uplift in performance.
Findings from the field
When companies scramble to innovate, they often fall into a predictable trap. Instead of building a clean, considered architecture, they pile third-party plugins onto their online commerce platform like Jenga blocks. My team and I see this failure pattern all too often. A brand wants a fast feature, so they install an app. Then they install another app to fix a limitation in the first one. Before long, a dozen different tools are fighting for control over the storefront code. This creates a brittle environment where a minor update in one tool breaks an entirely separate part of the site. It is an invisible tax on growth that paralyzes internal teams and destroys site speed.
My team and I recently reviewed a global enterprise account that illustrates this breaking point. On the surface, the business was ready for agentic commerce. Under the hood, third party app bloat had dragged their mobile score down to “Poor” on Google PageSpeed Insights. This fragmentation also buried their administrative teams under massive operational overhead, trapping employees in a constant loop of manual workarounds just to keep the storefront running. For example, instead of leveraging modern commerce automation features, each product recommendation block on the site had to be configured and updated completely manually by an admin. Attempting to launch agentic commerce customer experiences on top of an unstable architecture like that is a losing battle from day one.
Is your foundation ready?
The biggest risk for companies today is ignoring foundational gaps while jumping straight to highly visible AI use cases in the market. While much of the industry moves toward agentic experiences, tomorrow’s leaders are already preparing their data and architectures for that next wave of disruption. If you don’t fix the foundation today, your competitors will sprint ahead. You will be left playing catch-up for years to come.
If you remember only one thing from this article, let it be this: True digital transformation is unlocked when the patchwork ends.
Is your organization building capabilities for the future, or are you just duct-taping the past?
Stop guessing where the holes in your bucket are. At Globant’s Commerce Studio, we help global brands move past the patchwork, audit their technical debt, and build unified architectures designed for the upcoming wave of agentic AI.
