The future of AI is agentic, industry-sensitive, and hybrid by design. Discover what the early winners of the agentic era have in common, as well as what’s at stake for those who fall behind.
Enterprise AI has crossed a critical threshold. What began as scattered pilots has evolved into production-grade systems reshaping how organizations operate, compete, and scale. But progress is uneven and the gap between AI leaders and laggards is widening fast.
Hakkoda’s State of Data 2026 report reveals where enterprises stand today, what separates those scaling AI successfully from those stuck in fragmented deployments, and why hybrid-by-design architectures are emerging as the foundation for sustainable, enterprise-grade AI.
Drawing on executive insights and industry benchmarking from the IBM Institute for Business Value, the report explores how agentic AI is redefining operating models, why governance has become a catalyst for scale, and where infrastructure readiness is quietly determining winners and losers.
Key insights include:
- Enterprise AI has reached production, but not cross-enterprise maturity
Only 16% of organizations have operationalized AI enterprise-wide, while 41% remain stuck at the function or business-unit level. This maturity gap will define competitive advantage over the next 12–24 months.
- Agentic AI ambition is outpacing infrastructure readiness
While 72% of executives expect agentic AI to transform business models and 80% plan to increase investment, fewer than one-third have the interoperability and scalability required to support autonomous systems.
- Governance is shifting from a blocker to a growth lever
Organizations with mature AI governance report stronger security, faster adoption, and up to 27% of AI efficiency gains tied directly to governance practices.
- AI investments are paying off (but failure remains costly)
84% of executives report AI met or exceeded revenue expectations, yet 30% of initiatives failed to scale or were cancelled, most often due to skills gaps, security concerns, or weak governance.
- Hybrid-by-design architectures are proving foundational to agile, scalable AI
Leading enterprises are using hybrid architectures to balance elastic compute, regulatory control, and ecosystem connectivity. This translates into faster, safer scaling capabilities for agentic AI.
