Lawler Model

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The Top 5 Reasons Why AI Initiatives Fail

Carsten Krause 0 Comments 27 min read

The complexities of AI transformations can lead to significant challenges and unmet expectations. Unveiling the reasons behind failure, the article highlights misalignment with business objectives, data quality challenges, a widening skills gap, underestimation of integration complexity, and the proliferation of AI use cases as key obstacles. These issues are addressed through strategic alignment, prioritizing data quality and literacy, bridging the skills gap, and prioritizing seamless integration and robust governance. Real-world examples underscore the importance of these strategies in navigating the complexities of AI transformations successfully. We are evaluating why AI initiatives fail and what the lessons learned are that business leaders can learn from.

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AI StrategyDigitalFrameworksLawler ModelLLMProduct Management

The Lawler Model for Designing AI Products: A BloombergGPT Case Study

Carsten Krause 0 Comments ,  ,  16 min read

The advent of BloombergGPT is more than just a technological marvel—it’s a shift in how we understand the application of AI in finance. It represents the culmination of years of research, collaboration, and fine-tuning to create a tool that doesn’t just understand finance but thrives in it. As CDOs and tech leaders evaluate tools to bring their operations into the future, BloombergGPT stands as a compelling benchmark of what is achievable. It’s not just about automating tasks; it’s about enhancing decision-making, improving security, and ultimately, driving profitability. In a nutshell, BloombergGPT is not the future of financial technology; it is the technology that will build that future.

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