AI can bring enormous power and acceleration to business growth. Yet, as with any data-driven tool, it can also mislead, propagate biases, and create reputational, privacy, and security risks for the business. After all, bad data leads to bad AI and bad AI can lead to bad business outcomes.
These outcomes may range from bottom-line impact from wasting money on useless AI initiatives to making bets on business decisions backed by AI magic yet not grounded in reality—going all the way to front page news when confidential information gets leaked.
Conversely, done right, AI can lead to new product and market discovery, surpassing the competition, and unprecedented business growth.
What does it take to do AI right? Does getting data right for AI require the same steps and capabilities that accurate and prompt financial reporting or customer analytics does?
In this session we will cover the following topics:
- What is AI?
- When is AI an appropriate tool to use?
- Leveraging foundational data capabilities
- AI-specific data concerns and how to address them