Prioritization: Focus on small wins first. Do not overhaul systems or have multi months larger initiatives.  Just simple use cases where returns are evident. Also prioritize internal use cases first before customer facing ones. Human Resources queries or help desk chat bot for internal employee over for external customers. This will provide insights into what we will face while going external.

Governance: Run a Center of Excellence (CoE) and define an AI Program. Identify key stakeholders from various parts of the organization and make them part of the CoE.  Having a CoE provides visibility, clarity and governance structures to smoothly run the AI Program.

Existing Systems Impact: This is case by case. Some use cases may require integration vs. some may require replacing the older system. Some of the considerations are the degree of existing technical debt, cost of integration, cost to replace, and user training. If the degree of technical debt is less and implementing GenAI as a separate module is achievable, then always prefer Integration route.

Talent Impact: Like any change program, it will impact the existing resources. Define new job descriptions which are required to run the new paradigm and train selected internal people for the job descriptions. Often, it is cost effective to train internal vs hiring new resources and removing outdated resources.

Buy-In: Use all available methods to communicate your intention and advantages of the program clearly and throughout the organization. Sceptics will be there, however focusing on small and familiar use cases will help build trust and buy-in. Having new job descriptions and available training will also provide a career path for employees and bring buy-in.

Expertise: Engage a third party for expertise at the beginning and have them train your internal staff. Having a defined goal and intermediate milestones to transition the operations and ownership to internal teams is key.