How Purchasing Proven Solutions Doubles Your Chances of Success Compared to Building Your Own
AI is everywhere in retail, but implementing it successfully is another story. When companies consider AI, they face a key decision: build a solution in-house or buy a ready-made solution? While building your own AI might seem like the path to full control, the reality is often far more complicated—and riskier.
Why In-House AI Projects Often Struggle
Developing AI internally is resource-intensive. Skilled developers are scarce, model training takes time, and maintaining and updating the system adds ongoing costs. Many projects stall because AI tools lack persistent memory and feedback optimization, making it hard to adapt to real-world operations.
Simply put, it’s not about the AI’s capabilities—it’s about whether it can integrate smoothly into daily workflows and improve over time.
MIT Study Shows Buying AI Leads to Higher Success
MIT’s NANDA project recently studied AI adoption in business and found a clear pattern: companies that purchase AI from experienced vendors and collaborate closely with them succeed about two-thirds of the time. In contrast, in-house projects only succeed one-third of the time 1. The lesson is simple: partnering with experts dramatically reduces risk and speeds up results.
Viscovery: AI That Learns On the Job
Consider checkout operations. Viscovery’s AI image recognition system is already deployed in bakeries, pastry shops, and foodservice establishments across Japan, Korea, Singapore, Malaysia, and Taiwan. Unlike many generic tools, it learns from feedback, continuously improving accuracy and adapting to the specific products and workflows of each store.
Retailers don’t need to collect huge datasets or maintain algorithms themselves. Viscovery handles the heavy lifting, letting staff focus on improving customer experience and store efficiency. The payoff: faster checkouts, fewer errors, and happier customers.
The Bottom Line: AI Works When It Delivers Results
The value of AI isn’t in owning a custom-built system—it’s in deploying it effectively to create measurable impact. Proven, adaptive solutions like Viscovery help retailers see results quickly while minimizing risk. For companies that want to move fast and avoid costly trial-and-error, buying a market-tested AI solution is the most practical way to turn AI into a growth driver.
[Reference]
1 “MIT report: 95% of generative AI pilots at companies are failing.” FORTUNE, https://fortune.com/2025/08/18/mit-report-95-percent-generative-ai-pilots-at-companies-failing-cfo/. 18 Aug. 2025. Accessed 25 Aug. 2025.