[DSC DACH 25] Uros Miletic - Common pitfalls in AI adoption.pptx

Curious about the challenges of integrating AI into your organization? While AI technologies offer immense potential, they also present unique hurdles. In this session, we will explore the common pitfalls businesses face when adopting AI. We will discuss the right contexts for implementing AI solutions, how to avoid diving into complex projects too soon, and the importance of maintaining human oversight. Through real-world examples, we will highlight mistakes to avoid and best practices to ensure your AI initiatives succeed. This talk is ideal for business leaders, decision-makers, and professionals interested in the practical aspects of AI adoption. The insights shared will benefit both technical and non-technical audiences navigating the complexities of AI integration.

1. Common pitfalls in AI adoption

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4. Strategic & Organizational pitfalls Lack of clear business objectives No executive sponsorship Talent gaps Resistance to change

5. Technological pitfalls Inadequate data quality and availability AI is the easy part, product is the hard part Having no human-in-the-loop

6. Ethical, Legal & Governance pitfalls Lack of AI governance and accountability Ignoring ethical bias and fairness Privacy, compliance, and legal risks

7. Conclusion Define a robust AI strategy before jumping in Secure leadership buy-in and foster a shared vision Invest in people Invest in data cleaning, integration, and governance Ensure you have the right tools to support AI at scale Embed privacy and compliance measures into AI initiatives Establish a robust AI governance framework

8. Common pitfalls in AI adoption