What are some common challenges faced in AI projects?
Some common challenges include data quality, integration issues, and managing stakeholder expectations.
Can you elaborate on data quality issues?
Sure! Data quality issues can arise from incomplete, inconsistent, or biased data, which can lead to inaccurate models.
How can we overcome integration issues?
Overcoming integration issues often involves ensuring compatibility between systems and thorough testing before deployment.
What about managing stakeholder expectations?
Managing stakeholder expectations requires clear communication about project goals, timelines, and potential limitations.
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