Fri Sep 20 07:21:00 UTC 2024: ## AI Hype Meets Reality: Companies Struggle to Turn Generative AI Into Profit

**San Francisco, CA** – While the launch of ChatGPT in late 2022 ignited a frenzy for artificial intelligence (AI), the reality is that turning AI hype into tangible business benefits remains a challenge for many organizations.

According to Bloomberg Intelligence, the adoption rate of generative AI (GenAI) programs doubled between December 2023 and July 2024. Despite this growth, Deloitte reports that 70% of business leaders have only managed to move 30% or less of their AI experiments into production. Gartner predicts that 30% of GenAI projects will be abandoned after the proof-of-concept stage by the end of 2025.

This begs the question: why are companies struggling to capitalize on the potential of AI?

**Data Management is Key**

At the recent Snowflake Summit 2024, several business leaders shared their insights on successfully implementing AI. A common theme emerged: **data management is critical.**

Sasha Jory, CIO of Hastings Direct, stressed the importance of ensuring data is formatted in a way that AI can understand and utilize. Hastings leverages AI for tasks like underwriting and customer service, and Jory highlighted their success in automating processes, resulting in a 100% increase in speed to market and a threefold increase in underwriting changes.

Gerard Francis, firm-wide product head for data and analytics at JP Morgan Chase, emphasizes the significance of semantic consistency for unlocking AI’s potential with structured data. JP Morgan has invested heavily in building a common definition for business terms, ensuring AI can accurately interpret and analyze financial data.

**Human-AI Collaboration is Vital**

Anastasiia Stefanska, data analyst at TUI, emphasizes the importance of incorporating human oversight and governance in AI initiatives. TUI’s approach centers on employee empowerment, encouraging them to suggest use cases while ensuring that humans remain in the loop for decision-making.

**Focusing on the Right Areas**

Ulf Holmström, lead data scientist at Scania Group, underscores the importance of careful selection of AI applications. Scania is exploring GenAI for internal support processes, demonstrating a strategic approach to identifying areas where AI can deliver the most value.

**Addressing the Challenges**

Miguel Morgado, senior product owner at Eutelsat Group, acknowledges the challenges of developing and deploying AI, particularly regarding the need for knowledge graphs to contextualize data and provide more nuanced answers. Eutelsat is actively working on integrating knowledge graphs with AI solutions to improve service delivery.

**Looking Ahead**

While the path to widespread AI adoption may be bumpy, experts agree that the technology holds immense potential. By focusing on data management, human-AI collaboration, and careful selection of applications, companies can pave the way for a future where AI drives innovation and competitive advantage.

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