For years, digital commerce strategy has been shaped by a binary: buy vs build. The rise of MACH architecture and composability made “build” the default answer. Flexibility was king and customization was the path to differentiation.
But today, that mindset is being challenged by economic pressure, shifting consumer behavior, and the sobering reality of AI adoption.
In this climate, the smartest commerce leaders aren’t asking “can we build it?” They’re asking “should we?”
The buy vs build reset
According to Gartner’s 2025 Hype Cycle for Artificial Intelligence, generative AI has entered the Trough of Disillusionment. The hype is fading. The pressure to deliver tangible results is rising. Enterprises are scaling back experiments that don’t show ROI, and the same scrutiny is being applied to every layer of the tech stack.
Most components of modern digital commerce landscape (CMS, search, PIM, shopping cart, OMS, etc) are now mature, standardized and commoditized. Building your own versions rarely delivers strategic value.
“The focus must shift to orchestration and innovation, not engineering what’s already solved.”
Ilya Antipin, Principal, Technology Consulting at Empathy Lab
Build what differentiates, buy everything else: rather than reinventing foundational systems, invest in areas that drive competitive advantage:
- Brand content that fuels external discovery across AI assistants and social platforms.
- Loyalty programs that personalize value and deepen relationships.
- Logistics and returns that match or exceed marketplace convenience.
These are the levers that shape customer experience and drive conversion. Everything else? Buy it, integrate it and move on.
AI adoption: from experimentation to execution
Gartner’s Hype Cycle makes it clear: the next phase of AI isn’t about chasing novelty. It’s about building responsibly, scaling pragmatically and aligning with business goals.
Here are the pillars of a solid AI adoption strategy:
1. Business case support
Every AI initiative must be tied to measurable business outcomes. Without clear metrics, AI becomes a financial black hole.
2. Human-centered, AI-enabled
AI should augment, not replace, your workforce. Empower employees with tools that enhance productivity and decision-making.
3. Training-heavy rollout
Dropping AI into workflows without training leads to resistance and productivity dip. Invest in education, evangelism and change management.
4. Leverage vendor capabilities
Before building your own AI stack, explore what your existing vendors offer. Most platforms now include embedded AI features that are secure, scalable and cost-effective.
5. Data maturity
AI is only as good as the data it runs on. Invest in data quality, governance and infrastructure to ensure your AI initiatives are stable and impactful.
6. Start small, evolve fast
Avoid over-engineering. Launch focused MVPs, learn quickly and scale what works.
Build less, mobilize more
The future of commerce isn’t about owning every line of code, it’s about owning the outcomes. In the age of uncertainty – pragmatic approach, innovative mindset and disciplined execution will define winners.
Forget the hype, focus on value. Buy what works, build what matters, mobilize what converts.