The landscape of enterprise AI is transforming as organizations increasingly focus on AI applications, with nearly 70 percent of the effort in developing AI agents concentrated on data engineering. Srikanth Gokulnatha, senior vice president at Oracle, emphasized that effective AI solutions require a robust understanding of both unstructured and transactional data, moving beyond traditional data warehousing practices.
As companies adapt, the partner ecosystem is also evolving, shifting from conventional analytics to modern enterprise lakehouse architectures that support AI initiatives. This change necessitates a redefinition of value across data and analytics, with a greater emphasis on domain expertise and tailored go-to-market strategies. Many enterprises struggle to pinpoint specific AI use cases, presenting an opportunity for partners to create focused agent portfolios.
Gokulnatha noted a significant shift in how partners approach AI projects, moving from a data preparation-first model to one that begins with understanding business requirements. This evolving strategy highlights the urgency for partners to align their solutions with the increasing demands and advancements in AI technologies.