Trends
GenAI meets problems when implementing
Organizations are excited about generative AI’s potential to boost employee and business productivity, but they are unable to fully realize its potential due to a lack of talent and a lack of strategic planning, according to a study conducted in early 2024 by Coleman Parkes Research and sponsored by…
Headline
Organizations are excited about generative AI’s potential to boost employee and business productivity, but they are unable to fully realize its potential due to a lack of talent and a lack of strategic planning, according to a study conducted in early 2024 by Coleman Parkes…
Context
Organizations are excited about generative AI’s potential to boost employee and business productivity, but they are unable to fully realize its potential due to a lack of talent and a lack of strategic planning, according to a study conducted in early 2024 by Coleman Parkes Research and sponsored by data analytics firm SAS. Gaining confidence in the use of data while attaining compliance. Just 10% of organizations have a robust system in place to assess the risk of bias and privacy in LLMs (large language models). Furthermore, the majority of U.S. businesses are at risk of non-compliance with regulations, and 93% of them lack a thorough governance framework for GenAI.
Evidence
Pending intelligence enrichment.
Analysis
Incorporating GenAI into current procedures and systems. Organizations admit that integrating GenAI with their present systems is giving them compatibility problems. Aptitude and proficiency. Internal GenAI is deficient. Organizational executives are concerned that their HR departments may not have access to the skills needed to maximize their investment in GenAI as a result of a shortage of qualified candidates. Estimating expenses. Leaders point out that using LLMs comes with prohibitive direct and indirect costs. The token cost estimate provided by model creators is now recognized by organizations as being prohibitive. However, preparing private knowledge, training, and managing ModelOps come at a long and complicated cost. 300 US GenAI strategy or data analytics decision makers were surveyed Early in 2024 by Coleman Parkes Research, with funding from data analytics firm SAS. The purpose of the survey was to identify key areas for investment and the challenges that organizations are facing.
Key Points
- Organisations are enthusiastic about generative AI’s potential, but they are hitting stumbling blocks in 4 key areas of implementation.
- The study has surveyed 300 US GenAI strategy or data analytics decision makers to pulse-check major areas of investment and the hurdles organisations are facing.
- GenAI should be treated as an ideal contributor to hyper automation and the acceleration of existing processes and systems rather than the new shiny toy that will help organisations realise all their business aspirations.
Actions
Pending intelligence enrichment.
