Although AI was recognized as strategically essential before generative AI became distinguished, our 2022 survey found CIOs’ ambitions limited: while 94% of organizations were using AI not directly, only 14% were aiming to realize “enterprise-wide” AI by 2025. Against this, the facility of generative AI tools to democratize AI—to spread it through every function of the enterprise, to support every worker, and to have interaction every customer —heralds an inflection point where AI can grow from a technology employed for particular use cases to 1 that really defines the trendy enterprise.

As such, chief information officers and technical leaders can have to act decisively: embracing generative AI to seize its opportunities and avoid ceding competitive ground, while also making strategic decisions about data infrastructure, model ownership, workforce structure, and AI governance that can have long-term consequences for organizational success.
This report explores the newest considering of chief information officers at a few of the world’s largest and best-known corporations, in addition to experts from the general public, private, and academic sectors. It presents their thoughts about AI against the backdrop of our global survey of 600 senior data and technology executives.

Key findings include the next:

• A trove of unstructured and buried data is now legible, unlocking business value. Previous AI initiatives needed to deal with use cases where structured data was ready and abundant; the complexity of collecting, annotating, and synthesizing heterogeneous datasets made wider AI initiatives unviable. Against this, generative AI’s latest ability to surface and utilize once-hidden data will power extraordinary latest advances across the organization.

• The generative AI era requires an information infrastructure that’s flexible, scalable, and efficient. To power these latest initiatives, chief information officers and technical leads are embracing next-generation data infrastructures. More advanced approaches, reminiscent of data lakehouses, can democratize access to data and analytics, enhance security, and mix low-cost storage with high-performance querying.

• Some organizations seek to leverage open-source technology to construct their very own LLMs, capitalizing on and protecting their very own data and IP. CIOs are already cognizant of the restrictions and risks of third-party services, including the discharge of sensitive intelligence and reliance on platforms they don’t control or have visibility into. Additionally they see opportunities around developing customized LLMs and realizing value from smaller models. Probably the most successful organizations will strike the precise strategic balance based on a careful calculation of risk, comparative advantage, and governance.

• Automation anxiety shouldn’t be ignored, but dystopian forecasts are overblown. Generative AI tools can already complete complex and varied workloads, but CIOs and academics interviewed for this report don’t expect large-scale automation threats. As an alternative, they consider the broader workforce will probably be liberated from time-consuming work to deal with higher value areas of insight, strategy, and business value.

• Unified and consistent governance are the rails on which AI can speed forward. Generative AI brings industrial and societal risks, including protecting commercially sensitive IP, copyright infringement, unreliable or unexplainable results, and toxic content. To innovate quickly without breaking things or getting ahead of regulatory changes, diligent CIOs must address the unique governance challenges of generative AI, investing in technology, processes, and institutional structures.