The AI Failure Handbook

Across industries, companies are seeing their AI initiatives fail: some quickly, some quietly. Leading experts estimate 70-90% of AI projects fail to deliver the promised results, and the gap between promise and practice is where frustration and mistrust grows. 

For departments like finance, where tolerance for ambiguity is slim, trust in the technology means the difference between success and failure. When your team requires reliability over novelty, consistency over creativity, and transparency over possibility, automation that can't tell you when it's wrong will cost you more than it saves.

Read the ebook to understand the impact of these five failure patterns in financial automation:

• General AI solutions for specific tasks

• A lack of accountability loops

• Black-box decision making

• Inability to contain complexities

• The ownership gap