About
Generative AI (GenAI) is a revolutionary technology poised to transform industries. Organisations that effectively harness its potential will gain a significant competitive advantage. However, while many companies are exploring GenAI use cases, few are successfully implementing them. The primary obstacle lies in the lack of a comprehensible artificial intelligence strategy. A comprehensible strategy ensures that AI systems are transparent, understandable, accountable, and deliver tangible value to customers.
Based on our discussions with over 50 industry leaders, we've identified several key challenges hindering GenAI adoption. Chief among them is an overarching data management challenge – ensuring quality, consistency, and security of data from disparate sources is essential for effective GenAI implementation.
Other challenges hindering GenAI adoption include:
- Large language model (LLM) limitations: Current LLMs are primarily designed for unstructured text data, limiting applicability to certain tasks. Business AI problems require specialised machine learning (ML) models to handle numerical data and complex reasoning.
- ROI uncertainty: Quantifying the return on investment (ROI) of GenAI projects can be difficult, making it challenging to secure funding and support.
- Safety and trust: Addressing concerns about bias, fairness, and the potential for misuse of GenAI is essential for building trust.
- Capability and cost considerations: Balancing the cost of deploying and maintaining GenAI systems with their capabilities is a critical consideration.
CIONET, in association with Hitachi Digital Services, is convening an executive roundtable to address these key issues. We will explore the barriers to data coherence and consolidation and the practical steps forward.
Among the issues, we’ll discuss:
- Planned adoption of GenAI
- Where data consolidation sits on your list of priorities
- What steps you have taken to bring your data together
- The barriers preventing successful implementation
- Planned cross-industry sharing of LLMs
- Measuring ROI
- Safety and trust: the use and misuse of AI
Do join us for what promises an interactive, informal and insightful conversation among
peers.
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