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AI agents are seen as the next wave of enterprise automation, but over the past year, most companies are still exploring suitable adoption processes. Incomplete governance frameworks, insufficient security protections, low technological maturity, and employee change management have become major barriers. Based on KPMG surveys, Gartner forecasts, and insights from executives at multiple companies, this article explores how enterprises can prudently advance their AI agent strategies.
Actian's 2025 Data Governance Maturity Report indicates that corporate executives are overly confident in their data strategies, with actual data maturity assessments being 12% higher than those of daily data workers. Nearly 90% of data professionals report scaling and complexity issues, and over 80% face governance and compliance problems. Experts warn that weak data frameworks will erode trust, drive up costs, and hinder the deployment of agentic AI.
As enterprises accelerate their adoption of AI, data quality becomes the key to success or failure. This article reveals the three major costs of the "good enough" data strategy—employees lose 11.6 hours per week, enterprises lose an average of $15 million annually, and 70% of enterprises with data silos have experienced breaches—and points out that only 20% of AI projects succeed due to data issues. CIOs need to replace fragmented architectures with a unified data platform to gain a competitive advantage in the AI era.
On Wednesday, Databricks added agent-building capabilities and no-code data pipeline tools to its enterprise AI portfolio, and at its annual Data + AI Summit held last week in San Francisco, announced expanded cloud partnerships with Microsoft and Google Cloud. Agent Bricks, currently in beta, helps customers process unstructured data, build knowledge-assistant chatbots, and orchestrate multi-agent applications; the no-code tool Lakeflow Designer entered private preview. Additionally, Databricks extended its strategic collaboration with Microsoft, adding new Azure AI Foundry and Power Platform integrations, and plans to launch SAP Databricks on Azure within the year; its partnership with Google Cloud brings Gemini large models into the Databricks ecosystem.
Snowflake announced a series of product updates on Tuesday at its annual Snowflake Summit event, aimed at restructuring its data cloud platform to support the adoption of enterprise-grade AI agents. These updates include the launch of Snowflake Openflow, a hybrid multi-cloud data ingestion service, Cortex knowledge expansion for third-party data mining pipelines, and AI-driven natural language analysis and data science assistants based on Snowflake Intelligence and Data Science Agent. Additionally, Snowflake announced the general availability of its Cortex AI SQL agent query tool and SnowConvert AI data modernization assistant. These moves follow Snowflake's announcement on Monday of its acquisition of PostgreSQL startup Crunchy Data.
SAP and Microsoft announced on Tuesday an expanded partnership, launching a joint migration acceleration program to drive enterprise adoption of the SAP Business Suite bundled products. The two companies also unveiled a series of platform integration solutions covering AI assistants, security tools, and data analytics services.
As generative and agentic AI deployments drive enterprises to strengthen governance, automotive retailer CarMax began a comprehensive overhaul of its data practices nearly a year ago. Abhi Bhatt, the company's vice president of technology, said the team focused on three goals—data accessibility, runtime, and cost optimization—completed a cloud migration with Snowflake, and is improving knowledge base access efficiency and productivity through tools such as Microsoft 365 Copilot and AI coding assistants.
A report released by Ivanti last week points out that data silos are widening the gap between the reality and goals of IT teams. The survey shows that over half of technology professionals believe security and IT data are isolated within their organizations, leading to slow security responses, low IT efficiency, and hindering the effective use of AI tools.
According to Domo's latest analysis, from March 2020 to March 2025, usage of six major cloud data warehouses rose from under 16% to over 33%, highlighting that enterprises are treating cloud data as key infrastructure in the AI era.
Since formulating its generative AI strategy in 2023, American Honda has continuously strengthened data governance and AI governance, promoting the safe and efficient application of AI within the organization through the establishment of a Responsible AI Committee, a unified data platform, and digital literacy training.