New research highlights talent shortages and strategic gaps in GenAI applications

U.S. businesses are enthusiastic about the potential of productive forms of artificial intelligence (GenAI) to improve their businesses and employee productivity, according to a recent study. Yet behind the heightened enthusiasm, leaders see gaps in understanding, a lack of strategic planning and a lack of talent as barriers to realizing and measuring the full value of technology.

Earlier this year, Coleman Parks Research, with support from SAS, surveyed 300 U.S. people making strategic or data analytics decisions about GenAI to explore the key barriers faced by investments and organizations in this sector. For the study, Coleman Parks also surveyed leaders outside the United States. These global results will be published later this year. The message that can be read in this US executive summary is a demonstration of the challenges and potential of GenAI: how to achieve competitive advantage.

SAS Strategic Artificial Intelligence Intelligence Marinela Profi stated: “Enterprises are realizing that large language models (LLMs) alone will not solve business challenges. GenAI should be viewed as hyperautomation and acceleration Conceptual contributors to existing processes and systems, rather than newfangled toys that help organizations achieve all their business ambitions, take the time to develop a progressive strategy and invest in technology that provides the integration and explainability that governs LLM that all organizations need to focus on. Key steps you should take before committing and getting 'locked in'"

Organizations hit roadblocks in four key implementation areas:

Increasing trust in the use of data. And achieving compliance is critical: only 1 in 10 organizations have reliable systems in place to measure bias and privacy risks in LLM. In addition, 93% of U.S. companies lack a comprehensive governance framework for GenAI, and most companies face the risk of temporary regulatory non-compliance.

Integrating GenAI into existing systems and processes may encounter compatibility issues, so teams may face some compatibility challenges when trying to integrate GenAI with their current systems.

With HR departments lacking the necessary skills and resources, organizational leaders worry they won’t acquire the necessary skills to make the most of their GenAI investments.

Leaders cited prohibitive direct and indirect costs associated with using LLM. The model creator can provide a command cost estimate that is prohibitive (organizations now realize that this is also prohibitive). But the costs of expertise preparation, training, and ModelOps management are lengthy and complex.

Experts said: "This will ultimately become a real-life application case to ensure that we can provide the highest value and solve human needs in a sustainable and scalable way. Through this research, we will continue to work on Helping organizations stay relevant, invest wisely, and remain resilient In an era where AI technologies are evolving almost daily, competitive advantage relies heavily on the ability to embrace the discipline of resilience.”

##This. The information was announced at the SAS Innovation Conference, a data and artificial intelligence experience for business leaders, technology users, and SAS partners.