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Coverage of panels from the invitation-only ALIGN AI Executive Summits.
See the 2027 eventAt ALIGN Chicago 2026, Dynatrace's Akash Kadakia explained why AI needs different operating disciplines than traditional software, and how tracing, scoring, audit, lineage and access controls let organizations scale AI with confidence.
By The AI Enterprise Magazine Team ·
By The AI Enterprise Magazine Team ·
By The AI Enterprise Magazine Team ·
By The AI Enterprise Magazine Team ·
At ALIGN Chicago 2026, Elder Research's Lisa Targonski explained how AI amplifies weak data and unmonitored systems, and offered a simple readiness check and practical steps for building a foundation that supports ROI.
By The AI Enterprise Magazine Team ·
At ALIGN Chicago 2026, an HPE keynote panel compared agents in logistics, banking, payments and healthcare, and agreed that governance, auditability and human ownership decide whether agents can be trusted.
By The AI Enterprise Magazine Team ·
At ALIGN Chicago 2026, IBM watsonx Orchestrate director Gargi Dasgupta argued that agent sprawl is an operating model problem and demonstrated how a control plane detects, fixes, evaluates and governs agents in production.
By The AI Enterprise Magazine Team ·
At ALIGN New York City 2026, Skyflow's Sam Sternberg argued that sensitive data is under 1% of AI context but nearly all of the risk, and described how detecting, tokenizing and governing that data at runtime lets AI use it without exposing it.
By The AI Enterprise Magazine Team ·
At ALIGN New York City 2026, Rubrik's Paul St Vil described how coding agents slipped past every guardrail in an early rollout, why human approval and rules-based detection fell short, and how Rubrik now uses an AI governance agent to judge intent at runtime.
By The AI Enterprise Magazine Team ·
At ALIGN New York City 2026, Deasy Labs' Kirk Haslbeck explained why AI assistants built on curated files struggle with real document stores, and how classification, quality checks and sensitive-data tagging fix it before data reaches the model.
By The AI Enterprise Magazine Team ·
At ALIGN New York City 2026, SAS's Saurabh Mishra argued that the next wave of enterprise AI will move beyond RAG and agents to operational decision systems that remember events, connect them over time and learn from past decisions.
By The AI Enterprise Magazine Team ·
At ALIGN New York City 2026, NetApp's Jeffrey Thompson explained why auditors and litigators will ask what data a model saw, how data copies slow evidence requests, and how versioning and point-in-time replay can make AI decisions defensible.
By The AI Enterprise Magazine Team ·
At ALIGN New York City 2026, leaders from DLA Piper, The Fitch Group, Omnicom and Teradata explained why context, not model power, decides whether enterprise AI works, and compared notes on RAG pipelines, knowledge graphs, MCP and data ownership.
By The AI Enterprise Magazine Team ·
At ALIGN New York City 2026, Sphinx AI CEO Rohan Kodialam argued that the hard part of agentic analytics is not the agent but the business context behind it, and described how to train, govern and maintain that context automatically.
By The AI Enterprise Magazine Team ·
At ALIGN New York City 2026, leaders from Synchrony, Alteryx and Evernorth Health Services compared notes on bounded agents, the work it takes to make them reliable, and how to approach memory, tool orchestration and observability.
By The AI Enterprise Magazine Team ·
At ALIGN New York City 2026, InsightFinder AI's Helen Gu explained why agents built on one or two foundation models are fragile, costly and risky, and made the case for decentralized multi-agent systems with real-time evaluation and monitoring.
By The AI Enterprise Magazine Team ·
At ALIGN New York City 2026, KMS Technology CTO Guy Merritt shared how his team built a role-based agentic platform for software delivery, with tiered agents, deterministic workflows and layered guardrails.
By The AI Enterprise Magazine Team ·
Enterprise AI scales when it is tied to a real problem, validated, observed and cost-controlled, not when the model is impressive. Leaders explain how.
By The AI Enterprise Magazine Team ·
Leaders from BlackRock, Dollar General and ManTech explain what it takes to run AI agents in production: bounded use cases, engineering discipline, governance and cost visibility.
By The AI Enterprise Magazine Team ·
