Unlocking the agentic enterprise with Open Data Infrastructure

Agentic AI is expected to reduce the labor required for many consulting deliverables, challenging traditional effort-based pricing while creating an estimated $200 billion market for services focused on AI outcomes, with many enterprises likely to rely on external providers to operate their priority use cases. The central constraint is presented as business context rather than model intelligence, since unreliable data, conflicting definitions, inadequate permissions, and weak governance have contributed to failed AI deployments and remain major obstacles to adoption. The proposed solution is Open Data Infrastructure, built on open table formats, shared metadata, lineage, semantic layers, and governance, which would allow organizations to use multiple data platforms and AI models without locking business logic into one vendor’s stack. Consulting firms are encouraged to shift from selling staff time toward designing governed AI workflows, managing AI costs, assessing client maturity, and creating reusable intellectual property such as reference architectures, agent patterns, and portable operational knowledge.

Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.