Sixty per cent of organizations say a single approach to governance of data and AI assets is “very important”, a new report by MIT Technology Review Insights revealed. This indicates struggles with a siloed data architecture as well as increasing and thornier security and compliance needs.
The report gathered insights from a survey of 600 technology leaders as well as in-depth interviews from industry heavyweights at AT&T, Databricks, Dell Technologies, Walmart and others.
Arsalan Tavakoli, co-founder and senior vice president of field engineering, Databricks, said, “CIOs are realizing that there’s a real cost to maintaining the different monolithic stacks they previously acquired in the cloud. It’s not just the systems but the glue between them and getting them all to work together, which is painful and duplicative. There’s now a strong push to simplify.”
This unified approach is especially critical as organizations kickstart their AI journey to transform their operations, explained John Roese, global chief technology officer at Dell Technologies.
“A modernized data infrastructure is essential to scale AI across the enterprise. AI is not just a new consumer of our existing data systems. It will need a set of technologies that are optimized to feed data into its models, exchange that data with other models, and curate what the models produce. All of those are new workloads.”
The report notes that many technology leaders who were interviewed see a unified approach as a long-term aim, and that, in the meantime, they are employing federative approaches to ensure maximum commonality of language and rules across different models. However, the need for consistent, secure, and scalable governance remains a unifying strategic thread.
The report also speaks to the importance of creating industry data ecosystems to bolster AI-led growth.
Sixty-four per cent of survey respondents say the ability to share live data across platforms is “very important,” while an additional 31 per cent say it is “somewhat important.”
Technology teams at insurers and retailers, for example, aim to ingest partner data to support real-time pricing and product offer decisions in online marketplaces, while manufacturers see data sharing as an important capability for continuous supply chain optimization.
“The growing realization of the power of data and the increasing vertical and horizontal integration of the value chain elevate data sharing to a much more strategic level,” said Tavakoli. “After all, sharing is the cornerstone of synergy creation.” CIOs, he added, are asking how they can share data without imposing restrictions on what technology they are going to use.
For example, 63 per cent of respondents across verticals believe that the ability to leverage multiple cloud providers is at least somewhat important. Seventy per cent feel the same about open source standards and technology.
Tavakoli advised, “You don’t know what technologies are going to be created. Don’t put your data in walled gardens; use open formats, open standards, and open specifications to preserve strategic flexibility.” The growing availability and popularity of open-source LLMs, for instance, presents new opportunities.
The report concluded that generative AI adoption, which is booming across enterprises of all sizes and industries, will not be a one-size-fits-all approach, but in every case, “value creation will depend on access to data and AI permeating the enterprise’s ecosystem and AI being embedded into its products and services.”
The key to AI growth will also be to get data into the hands of every employee, affirmed Tavakoli.
“Every C-level executive we talk to in every industry understands that data and AI must underpin everything the organization does, and reach every individual in the organization. That means getting data into the hands of all employees—from the most technical to the least— so all of them can play an active role in driving insights to improve operations, developing new products, and serving audiences better.”