Focus on Problem, Not Solution: Gain buy-in by prioritizing root cause analysis. Secure widespread understanding of the problem and its urgency, especially from finance and IT leaders, before selling your solution.

Prepare for Technical Scrutiny: Anticipate higher levels of scrutiny during vendor assessments. Be ready to discuss model performance metrics, training data, data handling processes, and security measures. Demonstrate your solution's effectiveness through in-depth case studies and technical expert presentations.

Demonstrate Partnership Value: Recognize that trust and data access require reciprocity. Expect requests for shared risk, integration support, and long-term governance to reflect the value and risk of the investment.

Scale Beyond the Sandbox: Develop a comprehensive scaling roadmap that extends beyond your technical stack. Showcase your process expertise and its ability to ensure solution scalability across the entire system, not just IT.

Manage ROI Expectations: Collaborate with system champions to set realistic ROI goals. Acknowledge that most AI failures are due to cost issues (direct and indirect), limited error tolerance, and infrastructural/operational challenges. Identify and leverage opportunities for incremental ROI alongside primary objectives.