Enterprise AI adoption is currently concentrated in large language models, edge systems, and agents for software development, process automation, and calendaring. However, businesses have not yet broadly extended these technologies into core functions such as inventory management and supply chains due to demanding security, governance, and data requirements.
Infrastructure remains a primary obstacle for companies moving beyond experimentation. Broadcom's VMware AI Factory, based on VMware Cloud Foundation, aims to simplify private AI deployment by automating the transition from bare-metal infrastructure to model deployment.
David Linthicum, founder and lead researcher at Linthicum Research, suggests that many companies are still in the early stages of figuring out infrastructure and costs. He notes that most enterprises are not yet ready for AI systems and are seeking partners to modernize their infrastructure for on-premises AI execution.
Linthicum also warns against the over-use of autonomous agents. He estimates that 95% of agentic AI applications he encounters do not require an agent-based architecture, often introducing unnecessary complexity, operational overhead, and security concerns without adding significant value.
