Implementing AI in operations and supply chain management is a complex process that requires careful planning and execution. Here's an outline of a potential implementation strategy, along with some key considerations:

1. Identify the Opportunities: Start by identifying where AI could have the greatest impact on your operations and supply chain. This might be in demand forecasting, inventory management, warehouse operations, logistics, or another area. Be clear about what problems you are trying to solve or what improvements you want to achieve.
2. Build a Multidisciplinary Team: Assemble a team with diverse skills, including data scientists, operations experts, IT professionals, and change management specialists. Each member brings a unique perspective that can contribute to the successful implementation of AI.
3. Data Quality and Management: AI systems rely heavily on data, so ensure you have high-quality, reliable data. Implement robust data management practices to ensure data accuracy, consistency, and security.
4. Choose the Right AI Technologies: Depending on your goals, different AI technologies may be suitable. For example, machine learning might be used for demand forecasting, while robotic process automation (RPA) could be used for automating repetitive tasks.
5. Pilot and Test: Before rolling out AI solutions widely, conduct pilot projects to test their effectiveness. This will allow you to identify any issues or challenges and make necessary adjustments before a full-scale implementation.
6. Training and Support: Ensure that employees are adequately trained to use the new AI tools and understand how these tools will impact their roles. Provide ongoing support to help employees adjust to the new systems.
7. Monitor and Adjust: Once the AI systems are implemented, monitor their performance regularly and make adjustments as needed. This might involve fine-tuning the AI models, addressing data quality issues, or providing additional training for employees.
8. Ethics and Compliance: Ensure that your use of AI complies with all relevant laws and ethical guidelines. Consider issues such as data privacy, fairness, transparency, and accountability.
9. Scalability: Plan for the future by ensuring that your AI systems can scale up as your business grows or your needs change.

Remember, implementing AI is not just a technological change, but also a cultural and organizational one. It requires a clear vision, strong leadership, and the active involvement of employees at all levels.