94% of technology leaders believe AI-generated code is higher quality when reviewed, but 78% report more incidents after deployment.
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We'll break down how that stack is actually built, from ingestion through to the serving layer, the architectural patterns enterprises are choosing between and what tends to go wrong once the pipeline is live and someone's dashboard doesn't match finance's spreadsheet.
We explore why hardware security is moving beyond component inventories towards provenance, attestation and verifiable trust across the hardware lifecycle.
How data governance, semantic layers and consistent metric definitions can prevent confident AI-driven data errors.
Move the meaning first and turn months of migration into weeks
A Semantic Approach to SAP BW Cloud Migrations
We report on why OpenAI has classified Astra at its Critical cybersecurity capability level and what safeguards are being introduced before release.
We explore how agentic data engineering shifts responsibility from pipeline implementation towards defining constraints, validation and engineering judgement.
Key Findings from the 2026 GenAI Code Security Report
PRIORITIZE, PROTECT, PROVE
Most security tools tell you what happened. Ent helps security teams understand why risky actions occur and intervene before they become incidents.
Understand intent, not just activity
The Pentagon’s GenAI.mil platform’s arsenal has gained OpenAI’s ChatGPT Mil and xAI’s Grok for Government, expanding personnel’s access to multiple AI models across the US Department of Defense.
The goal isn't simply to understand data governance as a set of policies and processes. It's to understand how those foundations need to evolve when data starts powering AI systems that can operate at unprecedented scale and speed.
We explore how coding agents are shifting the economics behind enterprise software procurement and changing what organisations may choose to build.
From investment prioritisation to benefits realisation, explore the top value management platforms that help enterprises turn strategic investments into measurable business value.
We explore how workplace exoskeletons could reshape robotics by augmenting human capability rather than replacing workers.
In this article, we'll break down why most LLM projects actually fail, and what the successful 5% are doing differently.
China is rapidly scaling humanoid robotics, but impressive demonstrations don't necessarily translate into enterprise adoption.
Pricing the risk is its own problem. There's little historical claims data to work from, and AI developers themselves are still mapping out what their systems can actually do.
Automated RCA is moving closer to operational action. We look at what infrastructure teams need to see before they can trust its conclusions.
“A real-time layer of continuous authorisation which revalidates an agent's access as it acts and catches behaviour. When this drifts mid-session, the protect capability enforces policy based on the intent of the user or the intent of the agent at that moment.”
Explore why so many enterprise LLM rollouts turn into risk issues, the pillars a strategy needs, and a practical framework you can use to build one without slowing adoption.
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