As organizations explore the potential of AI, information management practitioners may face the challenge of being perceived as roadblocks rather than facilitators. However, by aligning Generative AI initiatives with business goals and promoting intentional adoption, these professionals can pivot into a critical educator role.
To effectively educate stakeholders, information managers should leverage real-world examples that resonate with their audience. When making the business case for AI, provide practical use cases that illustrate how the technology could be applied within the organization. For instance, demonstrate how AI could streamline the hiring process by suggesting insightful interview questions.
Rather than lecturing solely on technical concepts, contextualize AI within familiar business scenarios. This approach helps stakeholders understand the practical implications and benefits of AI adoption. By grounding the discussion in relatable terms, information managers can bridge the gap between abstract technology and tangible business value.
Information management practitioners should confidently showcase their expertise in AI and related domains. By seamlessly incorporating relevant lingo and jargon into discussions, they can establish credibility and demonstrate their mastery of the subject matter. This positions them as knowledgeable educators who can guide the organization's AI journey effectively.
Effective education is a two-way street. Information managers should create an environment where both they and senior leaders can learn from each other. Encourage open dialogue, actively listen to concerns and perspectives, and be receptive to feedback. This collaborative approach fosters trust and ensures that AI initiatives are shaped by a diverse range of insights and experiences.
By embracing these strategies, information management practitioners can shed the perception of being roadblocks and instead emerge as invaluable educators, championing intentional AI adoption aligned with the organization's goals and needs.
This blog post is based on the transcript of an original AIIM OnAir podcast, recorded on April 22, 2024. Listen to the full episode. AIIM used the Pro version of Anthropic's Claude.ai to convert the transcript to a blog post and then the post was edited by AIIM staff and the author.