1. Prioritize AI-driven cloud architectures to redefine strategy
AI is becoming increasingly embedded in the way businesses do business. Next-generation cloud architectures that leverage the latest AI capabilities are powering modern business strategies. While most companies still view AI as part of their technology strategy (or worse, as disconnected AI initiatives across the enterprise), top performers are going all-in, integrating it into the business plan across all functions. Two-thirds of top performers (67%) tell us they have a formalized strategy, including an approach to identify, implement, and track AI usage across the organization. Only 37% of other companies say the same.
While responsibility for technology architecture and cloud engineering typically falls to the CIO and other technology leaders in an organization, the choices they make lay the foundation that enables AI-centric transformation and new business models. This is a consideration that needs to be made at the CEO level. It’s critical that CIOs partner with their CEOs, perhaps in new ways, to make the right technology choices and inspire the rest of their organizations. Together, you can set expectations and continually demonstrate how various AI initiatives are foundational to business strategy and growth.
Given the applicability and impact of AI across all areas of the business, every senior executive has an important role to play. In the near term, we expect to see more companies appointing AI CEOs to help establish that vision and drive strategy in collaboration with leaders across the business. We’re seeing this strategic collaboration happening in many areas. In the front office, for example, CIOs are partnering with CMOs to focus on hyper-personalization and loyalty ecosystems. At the same time, we’re seeing CROs look at how their sales teams are leveraging AI to accelerate deal cycles, organize proposals and presentations, and accelerate overall time to market for products.
In the middle office, CIOs work with C-suites and their teams—including procurement, customer service, risk, and sustainability leaders—using AI to modernize and streamline their processes, enabling the front office to better meet customer needs where they are. It also enables internal teams to run the business at a higher speed with less tech debt and cumbersome systems. In the back office, CIOs and their IT teams can implement new ways of working and reinvent back-end systems to accelerate delivery and drive business strategy.
By far the biggest difference in behavior between the top performers and the rest of the companies in our survey is that 72% of the top performers say they have fully adopted the cloud to modernize their data, compared to just 33% of the rest. By moving their data to the cloud and making it more easily digestible by large language models (LLMs), top performers are more likely to extract new value from their data as they integrate new AI capabilities.
Top performers are also more mature than others in other cloud engineering disciplines, by more than 2x the rate. For example, they are all cloud-first, meaning they have adopted it widely, for security (70% vs. 37%), AI (60% vs. 27%), migration (59% vs. 25%), application modernization (57% vs. 27%), native application development (57% vs. 24%), and industry solutions (54% vs. 25%), among others.
