Key Expectations to Maintain
Running an AI Pilot will require consistent engagement from your team. While our team will handle the technical development, your subject matter expertise and feedback are essential for success. Expect to commit time regularly, not just at the start and end of the pilot.
Change happens gradually. Early versions of the AI system will need refinement and may not immediately match your vision. This is normal and actually valuable – it helps us understand exactly how to tailor the system to your needs. The goal is progress, not immediate perfection.
Some processes may initially take longer than your current methods. This is temporary and part of the learning curve. As your team becomes familiar with the new system and we optimize based on feedback, efficiency will improve.
You’ll discover requirements you didn’t anticipate. The pilot will reveal new needs and considerations that weren’t obvious at the start. This is a valuable outcome that helps us build a better final solution.
Important Cautions
Data quality directly impacts results. If your existing data has inconsistencies or gaps, the AI system’s output will reflect this. Be prepared to discuss data quality issues openly so we can address them.
Not everything should be automated. Part of the pilot’s purpose is discovering which tasks benefit from AI and which are better left to human judgment. We may find that some planned features are better handled manually.
Your team’s workflow will change. While we minimize disruption, some adaptation will be necessary. Team members may need to learn new processes or modify existing ones. Clear communication about these changes helps reduce friction.
Privacy and security requirements may evolve. As we work with your data and systems, we may identify additional security needs. Be prepared to discuss and make decisions about security trade-offs.
Practical Considerations
Budget for indirect costs beyond the pilot fee:
- Staff time for training and feedback
- Potential temporary decreases in productivity during learning periods
- Internal IT resource time for integrations
- Data cleanup or preparation efforts
Timeline flexibility is essential:
- Technical challenges may arise that require additional development time
- Your team may need more time to adapt to new processes
- Integration with existing systems might be more complex than anticipated
- Data preparation could take longer than expected
Success Metrics May Evolve:
- Initial metrics might need adjustment as we better understand the system’s impact
- New benefits may emerge that we hadn’t anticipated
- Some expected benefits might prove less significant than others
- We may need to develop new ways to measure success
Remember that a pilot is fundamentally a learning process. The goal is not just to test a specific solution, but to understand how AI can best serve your organization’s needs. Being open to discovery and willing to adapt plans based on what we learn will lead to the most valuable outcomes.