What lessons have you learned from failed or less successful AI pilot projects that have informed your full-scale deployment approach?
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Director of Systems Operations in Healthcare and Biotecha month ago
From our experience, setting clear expectations with stakeholders about the AI's capabilities and potential return on investment is essential. AI is often perceived as a panacea, but it's important to manage expectations realistically. It's not just about the initial cost but understanding the total cost of ownership that can escalate if not properly managed. Clear communication about these aspects helps in aligning the AI project's goals with the business objectives and prevents future misunderstandings about its capabilities and costs.Global Digital Workplace Sr. Director, Global Technology & Security in Healthcare and Biotecha month ago
The foremost lesson is the critical importance of data quality. The adage "garbage in, garbage out" holds particularly true in the context of AI. If the input data is of poor quality, the results will inevitably suffer. Another vital aspect is the allocation of dedicated resources. AI projects cannot be sidelined or treated as an afterthought without compromising their potential and overloading the involved staff. Additionally, proper adoption and training are crucial. In our experience, implementing comprehensive training sessions and providing ongoing support significantly enhances the outcomes. Those who are more engaged in the training process tend to derive more benefits from the AI solutions.