New updates have been reported about K2view.
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K2view has released its 2026 State of Enterprise Data Readiness for GenAI report, positioning the company at the center of a critical gap between GenAI ambition and data infrastructure reality in large enterprises. Based on responses from 300 senior IT and data leaders at U.S. and U.K. organizations with more than 1,000 employees, the study shows that 45% plan early production GenAI deployments in 2026, up sharply from 2% in 2024, yet most still depend on analytics-era architectures not built for operational AI at scale.
The survey highlights that while responsible-use guardrails (76%) and workforce skills (66%) are the top overall concerns, executives cite enterprise data readiness (62%) and reliability of LLM outputs (52%) as the main technical obstacles to production GenAI. Within data readiness, the biggest issues are data quality and consistency (59%), fragmented data across systems (50%), data security and privacy (50%), and real-time data integration and access (33%), underscoring the need for governed, real-time data delivery that K2view’s Data Product Platform aims to address. Respondents currently lean on data warehouses (78%), systems of record (66%), lakehouses (58%), and vector databases (57%) as primary GenAI data sources, an approach K2view CEO Ronen Schwartz warns is insufficient for production workloads that require trusted, in-flow-of-work access to operational data. The report reinforces K2view’s strategic framing of its platform as an enabler of AI-ready, governed data products that can be reused across use cases such as agentic AI automation and customer service, supporting its positioning with large enterprise customers and its broader push to monetize GenAI-related data infrastructure demand.