Data governance is often seen as a cost center. Reframe it as an enabler of revenue by showing how trusted, standardized data reduces the "idea to insight" cycle. This allows executives to make faster, more confident decisions that drive growth and secure buy-in.
To overcome the fear of new AI technology, block out dedicated, unstructured "playtime" in your calendar. This low-pressure approach encourages experimentation, helping you build the essential skill of quickly learning and applying new tools without being afraid to fail.
When developing AI for sensitive industries like government, anticipate that some customers will be skeptical. Design AI features with clear, non-AI alternatives. This allows you to sell to both "AI excited" and "AI skeptical" jurisdictions, ensuring wider market penetration.
Standard application processes often filter out candidates with non-linear career paths. Bypassing these filters requires "warm networking"—building genuine connections with people inside a target company to let them see your potential as a human, not just a CV.
New AI tools often have flawed user experiences. Instead of just getting frustrated, create a detailed product breakdown with recommendations for improvement. Sending this to the company serves as a powerful "warm intro," showcasing your product skills and providing value before you're hired.
When lobbying for a new tool like telemetry, don't just ask for the tool. Frame its absence as a direct blocker to your core responsibilities. By stating, "I can't make decisions without this data," you tie the budget request to clear business outcomes and personal accountability.