Leaders admit a lack of governance framework; only 10% feel prepared for regulatory compliance

1. Enthusiasm vs. Challenges:

US organizations express enthusiasm for the potential of generative AI to boost productivity. However, beneath this optimism lie significant challenges related to understanding gaps, strategic planning, and talent shortages. These obstacles hinder the full realization and measurement of GenAI's value in organizations.

2. Importance of Strategic Planning:

Marinela Profi, Strategic AI Advisor at SAS, emphasizes the importance of strategic planning and viewing GenAI as a contributor to hyperautomation. Developing a progressive strategy and investing in technology that offers integration, governance, and explainability of large language models (LLMs) are essential steps for organizations before fully adopting GenAI.

3. Key Implementation Challenges:

The study identifies four key areas of implementation challenges:

   - Trust in data usage and compliance: Only a small fraction of organizations have reliable systems to measure bias and privacy risk in LLMs. Lack of comprehensive governance frameworks poses compliance risks.

   - Integration into existing systems: Compatibility issues arise when integrating GenAI with current systems.

   - Talent and skills shortage: Organizations struggle to find suitable hires with GenAI skills, impacting their ability to maximize GenAI investments.

   - Predicting costs: Organizations face prohibitive direct and indirect costs associated with using LLMs, including knowledge preparation, training, and ModelOps management.

4. Real-world Use Cases and Competitive Advantage:

Profi emphasizes the importance of identifying real-world use cases that deliver high value and address human needs sustainably and scalably. Competitive advantage in the evolving AI landscape hinges on organizations' ability to embrace resiliency rules and invest their resources wisely.

While US organizations recognize the potential of generative AI to enhance productivity, significant challenges exist in understanding, planning, and talent acquisition. Strategic planning, governance frameworks, and identifying high-value use cases are essential for maximizing the benefits of GenAI and gaining a competitive edge in today's dynamic business environment.