While the roadmap to deliver Gen AI change is clear, there are challenges that CIOs must first overcome to achieve the three key aims outlined above.
Firstly, “the relative infancy of the agenda presents a major challenge in that this is a new frontier for CIOs across the board,” says David, “bringing a plethora of learning curves along with it.”
He continues: “For example, it’s difficult to manage the voracious appetite of LLMs for data. The applicability of increasingly diverse data sets for Gen AI use cases increases the risk of inadvertent proliferation and exposure, leading to potential data security and privacy issues. Conversely, a lack of availability of data for use cases can stifle innovation with lost opportunity cost.
“We’ve also seen a new phenomenon we call ‘vendor confusion.’ Hundreds of vendors are offering models, data stores, libraries and other assets, which makes it hard to navigate and determine the combination that works best. There is also a lack of agreement on the highest-value use cases, which results in long periods of testing.”
Gen AI: A people, process and technology triumvirate
At its core, David says to successfully implement Gen AI, CIOs and IT…
