Dealing with stakeholders with diverse AI knowledge. How can you effectively manage their expectations?
Dealing with stakeholders with varying levels of AI knowledge can be challenging. To manage their expectations effectively, consider these strategies:
How do you handle stakeholders with different AI knowledge levels?
Dealing with stakeholders with diverse AI knowledge. How can you effectively manage their expectations?
Dealing with stakeholders with varying levels of AI knowledge can be challenging. To manage their expectations effectively, consider these strategies:
How do you handle stakeholders with different AI knowledge levels?
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First, focus on the business value that AI brings. For example, highlight whether AI will cut costs by X%, accelerate a proccess by Y days, create a new revenue stream with Z$, improve customer satisfaction. Second, clearly highlight why AI is part of the solution, point out its limitations and associated resources needed. Explain potential alternative solutions, maybe the alternatives are simplier to explain? Third, try to be clear about the risks and unknowns, timelines, and milestones. This will help you to avoid overselling and set realistic expectations. Finally, frequent communication on the progress, achievements and blockers in the project will tremendously help including updates on all the above-mentioned items if necessary.
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Managing stakeholder expectations in AI projects is crucial, especially when people have different levels of AI knowledge. Take a company like Google—technical teams need deep dives into models, but executives focus on how AI impacts revenue and strategy. Tailor communication: use simple analogies for non-tech teams, like comparing AI to decision-making tools, and focus on ROI when speaking to executives, like how AI helped Amazon improve customer recommendations. Use multiple channels to engage everyone—workshops for in-depth talks, newsletters for updates. Stay transparent about challenges, set clear goals, and invite feedback to keep everyone aligned and supportive.
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To manage diverse stakeholder expectations in AI projects, start with a knowledge assessment to gauge individual understanding levels. Develop a tiered communication strategy, using appropriate terminology for each group. Create visual aids and demos to illustrate AI concepts tangibly. Implement regular "AI 101" sessions to build a common knowledge base. Use concrete examples and case studies to demonstrate realistic AI capabilities and limitations. Establish clear, measurable project milestones to track progress objectively. By adapting your communication approach and fostering a shared understanding of AI, you can effectively align expectations across stakeholders with varying AI knowledge levels.
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Set Clear and Realistic Expectations: Make sure all stakeholders understand AI’s capabilities and limitations. Avoid over-promising and clarify that AI is not a magic solution, but a tool that requires proper data and fine-tuning.
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The stakeholders may benefit from some AI training to become more familiar with the technical concepts. To compliment this training, provide some hands-on exercises, where possible, to reinforce the training. It may also be helpful to have group sessions to surface differences in the team's understanding of AI, identify potential common points of understanding, and ways to bridge gaps.
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