The power of generative artificial intelligence (GEN AI) has organisations of all types intrigued and clamouring to leverage its functionality to enhance productivity, improve their financial bottom line and maintain market share or possibly achieve a competitive advantage. Increasing the speed and robustness of information assets presents ample opportunities for process applications. However, the jury is still out on a few issues for implementing this technology to achieve truly valuable results. Issues involving the data that must be accessible for large language models (LLMs), verifying the output generated and where to apply the platform to operationalise it for a sustained production environment introduces difficulties in its adoption.
The following steps provide a high-level methodology on how to best approach the implementation of GEN AI to produce effective results that
