Our take on:
Webinar: How to Use GenAI for Enterprise Analytics
- Dave Mariani, Steve Nouri and Arun Nandi @ AtScale
This session should be very instructive and insightful. Generative AI is shaping up to be a valuable asset in enterprise analytics if approached properly, producing cross-departmental insights which otherwise would have gone unnoticed. Analytics are also a key component in Generative AI deployment itself.
Both generative and predictive solutions (making use of LLMs) require accurate data sets and sound methodologies in order to produce reliable results. Market analysis and forecasting, research reports and financial projections all require data integrity and reliable sources. Generative AI demands a human-in-the-loop response and other integrations to validate its output from the black box.
The what, the why, the how and the intended audience should all be addressed, documented, and built into employee workflows to ensure compliance and response quality. In order to achieve these objectives, a governing policy, architecture and platform to effectuate, monitor and evaluate Generative AI use cases, while also containing risks, is also suggested.
Implementing such a system, equipped with its own analytics and monitoring, allows you to measure your use of Generative AI and gain new insights from your data with confidence.
About R. Scott Jones
I am a Partner in Generative Consulting, an attorney and CEO of Veritai. I am a frequent writer on matters relating to Generative AI and its successful deployment, both from a user perspective and that of the wider community.