Enterprise data and AI platforms move toward autonomy and agents
Enterprise data and AI platforms are integrated software environments that unify storage, processing, governance and machine learning to help organizations build applications, automate decisions and control AI systems at scale. This year’s flagship data platform announcements from Datadog, Databricks and Rubrik show a shift toward enterprise AI autonomy, AI agent development and unstructured data processing as strategic priorities. Together, these vendors are trying to answer a common problem: AI workloads and security risks are growing faster than humans can manage with manual tools. Their new capabilities span observability, agent platforms and AI-ready data layers, but share themes of tighter governance, richer context and more developer control. For enterprises, the message is clear: future competitiveness depends not only on better models, but on the operational control planes that surround them.
Datadog launches 100+ capabilities for AI autonomy and security control
At its DASH conference, Datadog introduced more than 100 new capabilities aimed at helping customers drive autonomy while managing rising AI and security complexity. Co-founder and CEO Olivier Pomel warned that AI has “created new operational challenges where code development has outpaced human-scale management,” highlighting the need for better operational control around models. A centerpiece of the announcements is Bring Your Own Cloud, which lets organizations deploy the Datadog platform into their own environments so telemetry is processed and indexed in their cloud object storage rather than moved into a separate service. This addresses the cost and visibility trade-offs caused by exploding log volumes in AI-heavy systems. Datadog is also evolving Bits AI, its suite of agents for development, security and operations, toward more autonomous behavior that can not only diagnose incidents but also take actions within controlled boundaries.
Databricks’ Data + AI Summit and Agent Bricks push AI agent development
Databricks is using its Data + AI Summit to underline its position as a central hub for AI agent development and data intelligence. The event is set to host more than 30,000 in-person attendees and tens of thousands more online, with 800+ breakout sessions covering data engineering, governance, analytics, applications, agents and AI. On the product side, Databricks is expanding Agent Bricks from an experimental toolkit into a full agent platform. The company says developers discovered that the core agent loop is only a small fraction of the work, with the “other 99%” tied up in token capacity, deployment, security, monitoring and context management. The new Agent Bricks focuses on three pillars: model choice across proprietary and open-source options, better context access over messy data estates, and stronger control over privileged agents, their access and their costs. Databricks’ pitch is that a unified data and AI platform is needed to govern both agent inputs and outputs.
Rubrik Annapurna targets AI-ready unstructured data without duplication
Rubrik’s Forward conference put the spotlight on unstructured data processing as a blocker for enterprise AI. The company’s Annapurna initiative positions Rubrik as an “AI-ready unstructured data layer” for any chosen Data Intelligence platform. Operating on Rubrik Security Cloud, Annapurna auto-discovers and scans unstructured file estates across NAS, S3 and object stores, then publishes a queryable catalog of file metadata into a lakehouse in hours instead of weeks. Rubrik notes that unstructured data represents 90% of many enterprise footprints, but most of it remains siloed, untracked and unreachable for AI because of costly extract, transform and load pipelines and duplicated environments. “Annapurna completely inverts that model. It activates data right where it lives,” said CPO Anneka Gupta, arguing that aligning infrastructure costs to actual consumption is key to scaling AI. For AI teams, this promises AI-ready context without moving or transforming entire file estates.
What these announcements mean for enterprise AI governance and flexibility
Taken together, the latest announcements point to a new phase in enterprise AI autonomy. Datadog is building an observability and security control plane that can keep pace with AI-driven systems, Databricks is turning Agent Bricks into an opinionated but flexible platform for agents, and Rubrik is making unstructured data first-class fuel for AI without duplication. For CIOs and data leaders, the common threads are governance, accessibility and developer flexibility. Better governance comes from unified platforms that handle monitoring, security and evaluation for both models and agents. Data accessibility improves as Bring Your Own Cloud and Annapurna let enterprises keep data where it is while still making it queryable for AI. Developer flexibility is reinforced by Databricks’ focus on model choice and control. These moves suggest that future competitive advantage will come from how well enterprises combine data, agents and control rather than from models alone.
