As enterprise AI adoption grows, the partner ecosystem faces significant structural changes. Traditional revenue models tied to analytics and data warehousing are evolving towards AI-led applications and modern data architectures. The focus is no longer just on integrating AI but on redefining value creation across data, analytics, and application delivery. Experts emphasize that data engineering constitutes about 70% of AI project work, indicating its importance in developing AI solutions. Partners must shift from a data preparation-first approach to embedding themselves within client businesses to define specific AI outcomes. With advancements in large language models, partners need to continuously adjust and adapt their offerings, moving towards agentic AI competence and data science skills through Centres of Excellence. Finally, reporting is transitioning to AI-powered experiences, with an emphasis on modern data architecture and a deep understanding of evolving language models. This positions partners to leverage reusable domain IP for mission-critical AI deployments.
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