Data silos aren't just an IT headache — for business leaders, especially those in customer insights, they're a direct threat to the quality and speed of decisions that reach the business. When research findings stay trapped in one team, or customer feedback never makes it into product discussions, the entire value of the insights function gets undermined.
Andrew Reid, CEO and Founder at Rival Technologies, recently tackled this challenge head-on in Entrepreneur. His article was written for entrepreneurs in particular, but many takeaways apply to business leaders and heads of insights. Here's a recap of the key points.
The technical excuses are gone
At last year's AWS re:Invent conference last year, one thing stood out to Andrew: security, compliance, and governance tools now make safe data sharing possible without slowing decisions down.
"The technical limitations that once justified locking data down have largely been solved," Andrew notes. "What remains difficult is human."
For insights leaders, this matters. The argument that it's "too risky" or "too complex" to share data across teams no longer holds. The barrier is organizational will, not capability.
Everything is data now
AI has dramatically expanded what counts as usable data. Customer reviews, survey verbatims, social signals, operational workflows — signals that were once treated as noise can now inform real decisions.
This is particularly relevant for insights teams. For many companies, conversational surveys, insight communities and other ongoing agile research programs are a source of unstructured data.
Andrew points out that all this data is a goldmine for AI agents.
"The posture a company takes toward sharing and using this information now determines its competitive edge," Andrew argues.
The real barrier is culture
"Alignment, trust and confidence inside organizations are now the true barriers," Andrew writes — and insights leaders will feel this acutely. Research teams often produce rigorous work and deliver a lot of rich data and insights. The challenge now is how to open up all that data with the right strategy to win in the AI race.
The organizations winning on this have made sharing the default.
"AI won’t force people to cooperate," Andrew points out. "Governance frameworks won’t create trust. Leaders must address the human side first."
What business and insights leaders can do now
Andrew outlines a practical path forward that maps well onto the insights function specifically:
Audit what you're actually sitting on. Most insights teams collect far more than they activate. Syndicated data, CRM signals, community feedback, qual archives — AI can help surface where untapped value exists, but only if you're looking.
Make sharing a stated expectation, not a courtesy. Set norms that data sharing is required and that findings will be used responsibly. Trust has to be built deliberately — especially in organizations where past data misuse (even minor) has made teams protective.
Move now. As Andrew puts it: "Companies that engage early, establish best practices and shape how data is used will define their market. Those who wait will struggle to catch up."
For insights leaders, being early means shaping how AI-powered research gets adopted inside your organization — not reacting to it after the fact.
The infrastructure is ready. AI is ready. What separates insights functions that drive real business impact from those that produce reports nobody reads is the same thing Andrew identifies: solving the human problem first.
For more on this topic, check out Andrew's article in Entrepreneur.
Looking to incorporate agentic AI into your research practice? Check out Rival's quick guide for best practices and tips.
