"Most enterprises are applying AI to systems that support employees but are not central to operations, such as calendaring and customer messaging, rather than to core applications."
"AI is most often used in IT, marketing, and sales, with common use cases including content support and customer service automation, but many organizations remain in pilot mode."
"Only 39% of organizations report any enterprise-level earnings impact from AI, highlighting that while adoption is broad, deep transformation in core business areas is limited."
"The distinction between edge and core applications is critical, as most AI efforts focus on systems that are easiest to automate rather than those that define operational performance."
Enterprise AI is primarily implemented in non-core systems, such as employee productivity tools, rather than in critical operational areas. This misalignment results in limited meaningful adoption and transformation. Core applications, including inventory management and financial processing, are essential for business performance. Current AI usage is concentrated in IT, marketing, and sales, with many organizations still in pilot phases. Only a small percentage report significant enterprise-level earnings impact, indicating that while AI adoption is widespread, its integration into core business functions remains insufficient.
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