agentic AI

Enterprise AI Readiness Gap: Why 90% of Firms Aren't Ready

Enterprise AI Readiness Gap: Why 90% of Firms Aren’t Ready

Agentic AI, AI Governance, Application Development, Digital Transformation /

Publicis Sapient’s 2026 Global Enterprise AI Report surveyed 1,550 decision-makers and found that AI is embedded in daily enterprise work, yet organizational readiness has not kept pace. Only 10 percent of organizations describe AI as core to operations, and 42 percent say their firms are not built to capture the value AI can already deliver. ECI Research analysis identifies governance gaps and workflow fragmentation as the defining barriers to closing the readiness gap.

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Airbyte 2.1: Building the AI Data Movement Layer Enterprises Need

Airbyte 2.1: Building the AI Data Movement Layer Enterprises Need

AI, Application Development, Cloud-Native, Infrastructure /

Airbyte released version 2.1 of its data movement platform alongside a Forrester TEI study showing 239% ROI. ECI Research analysts examine the business case, competitive positioning, and what the Airbyte Agents initiative signals about where enterprise AI data infrastructure is headed.

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CloudZero Bets on AI Spend ROI as CFOs Demand Proof

CloudZero Bets on AI Spend ROI as CFOs Demand Proof

AI, Application Development, Cloud, FinOps /

CloudZero has rebranded as the AI ROI Company, expanding its cloud cost allocation engine to connect AI token spend, agent workflows, and model costs to business outcomes. With only 14% of CFOs able to prove AI ROI, the platform addresses a financial visibility gap that is becoming a board-level issue. ECI Research examines what this means for ITDMs managing AI economics and developers building agentic systems.

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AWS NY Summit 2026: AI Infrastructure, Quantum & PQC Security

AWS NY Summit 2026: AI Infrastructure, Quantum & PQC Security

AI, Application Development, AWS Summit 2026, Events, Infrastructure, Machine Learning, Security /

AWS used its 2026 New York Summit to outline a full-stack AI and security infrastructure strategy spanning Graviton5 for agentic workloads, a fault-tolerant quantum computing partnership with QuEra, and expanded post-quantum cryptography across core managed services. The announcements reflect a deliberate shift from discrete compute services toward integrated infrastructure designed to support enterprise AI at scale. For ITDMs and developers alike, the session signals that security and compute architecture decisions made today will determine readiness for both the AI-native era and the post-quantum transition.

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Agentic AI Is Reshaping the SDLC: AWS Summit 2026

Agentic AI Is Reshaping the SDLC: AWS Summit 2026

AI, Application Development, AWS Summit 2026, Cloud, Events, Machine Learning /

At AWS New York Summit 2026, three enterprise customers demonstrated how AI tools including Kiro, Transform, and Bedrock Agent Core are compressing time across every phase of the SDLC. From spec-driven development to multi-agent production ecosystems, the event signaled a shift from AI as a coding assistant to AI as an operational backbone. ECI Research analyst coverage highlights what this means for ITDMs and developers navigating governance, modernization, and competitive pressure.

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AWS Agent Core: Building the Agentic AI Governance Layer

AWS Agent Core: Building the Agentic AI Governance Layer

AI, Application Development, AWS Summit 2026, Cloud, Enterprise IT Strategy, Events, Infrastructure /

AWS advanced Agent Core at its New York Summit with a policy gateway, portable workload identity, and context graph snapshotting designed to make agentic AI governable at enterprise scale. ECI Research analyzes what the announcement means for IT decision-makers navigating agent deployment risk and for developers building on existing frameworks. The core argument: governance infrastructure is becoming the competitive differentiator in agentic AI, not model capability.

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AWS Agentic AI Platform: Bedrock Agent Core, Q, and More

AWS Agentic AI Platform: Bedrock Agent Core, Q, and More

AI, Application Development, AWS Summit 2026, Cloud, Enterprise Software, Events, Infrastructure, Machine Learning /

AWS announced a sweeping set of agentic AI capabilities at its New York event, including the general availability of Bedrock Agent Core Harness, a new managed knowledge graph service called AWS Context, and a Release Agent inside AWS DevOps Agent. ECI Research examines what the announcements mean for enterprise IT buyers and developers navigating the prototype-to-production gap.

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Closing the Enterprise AI Context Gap | ECI Research

Closing the Enterprise AI Context Gap with Relational AI

AI, Application Development, Decision Intelligence, Enterprise Applications, Machine Learning /

The enterprise AI market is discovering that larger models don’t fix a broken context architecture. Relational AI CEO Molham Aref argues that closing the AI value gap requires executable, relational context grounded in business semantics. ECI Research examines the implications for IT decision-makers managing token economics and developers building production-grade agent systems.

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AWS Agentic AI Platform Shifts from Generation to Delivery | ECI Research

AWS Agentic AI Platform Shifts from Generation to Delivery

AI, Application Development, AWS Summit 2026, Cloud, Enterprise IT Strategy, Events /

AWS has unveiled a broad expansion of its AI platform, introducing continuous security remediation, autonomous background agents, and a unified data layer called AWS Context. The announcements signal a strategic shift from AI as a productivity tool to AI as a continuously operating enterprise system. ECI Research examines what the announcements mean for IT decision-makers and developers evaluating agentic AI investments.

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Omnigent: Databricks Open Sources an AI Agent Meta-Harness

Omnigent: Databricks Open Sources an AI Agent Meta-Harness

AI, Application Development, Cloud, DevOps, Machine Learning /

Databricks has released Omnigent, an open source meta-harness that sits above existing AI agent frameworks to enable composition, governance, and real-time collaboration across agents. The Apache 2.0 release targets a critical gap in enterprise agentic AI: each harness today is a silo with no shared control plane. ECI Research analysis examines what this means for IT decision-makers managing agent sprawl and developers building multi-harness workflows.

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