In this episode of Digital Transformation Bytes, Brad speaks to AI culture expert, Rosanne Werner, about why accurate, standardised data is critical to fuel the AI revolution for success.
AI relies on data to learn, predict, and optimise processes. But not all data is useful. Rosanne explains how businesses can determine what data matters most when setting up AI-driven processes. By focusing on structured, relevant, and high-quality datasets, companies can improve AI accuracy and drive better decision-making.
A key challenge in digital transformation is the presence of data silos – when valuable information is trapped in disconnected systems. Our experts highlights how breaking down these silos enables AI to access a complete, unified dataset, leading to more accurate insights and better automation. By integrating systems and ensuring seamless data flow, businesses can unlock the full potential of the AI revolution.
One of the biggest hurdles in AI adoption is eliminating bias. Whether intentional or unintentional, biased data can lead to unfair or inaccurate outcomes. In this episode, we explore practical strategies to reduce bias, such as:
- Ensuring diverse data sources
- Regularly auditing AI outputs
- Avoiding historical bias in training data
By following these best practices, businesses can build trustworthy and ethical AI systems that support digital transformation.
Join us for this insightful discussion on how the right data fuels AI innovation and how organisations can prepare for the future of AI-driven decision-making.
