Artificial Intelligence

Start With the Context Layer First: A Framework for Production-Ready AI Agents

Moving agents from demos to real workflows means treating the context layer as core data infrastructure, not a last‑minute integration.

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From Renders to Data Layers: How AI Is Reshaping Architecture’s Visualisation Stack

Roderick Bates, Head of Product Operations at Chaos, on how AI is compressing multi-stage design workflows, where the company drew the line on automation, and why visualisation platforms are quietly becoming architecture's data backbone.

From Chatbots to Persistent Agents: What Voice AI Taught Us About Infrastructure Limits

As agents evolve from endpoints into always‑on processes, voice and agentic workloads reveal why tomorrow’s AI systems need process‑centric, stateful infrastructure.

Disrupting Threats Before They Materialise: AI’s Expanding Role in Investigations

AI is enabling investigative teams to move beyond reactive casework — surfacing risks earlier, structuring fragmented data, and shifting the function upstream toward disruption.

Middle East: The Sovereign AI Testbed US, EU and Asia Can Learn From

Driven by massive capital deployment and a "Sovereign AI" mandate, the Middle East is transitioning from a technology consumer to a foundational infrastructure provider. By 2030, regional data center capacity is expected to triple, supported by strategic partnerships with OpenAI, Microsoft, and AWS.

Agentic AI in Production: Why Better Prompts Won’t Bridge the Gap

The pilot-to-production gap in agentic AI isn't a model problem, but an architecture and governance problem. Here's what the fix actually requires.

NVIDIA’s VP of Solutions Architecture on What It Actually Takes to Build a Sovereign AI Factory

Saudi Arabia is scaling toward 500-megawatt AI campuses. Deutsche Telekom is building a billion-euro Industrial AI Cloud in Munich. But the hardest part isn't the money — it's the architecture. NVIDIA's Marc Hamilton on the first 90 days of a sovereign AI factory build.

NVIDIA GTC 2026: From GPUs to AI Factories

From agentic operating systems to shifting inference economics, we break down the most critical enterprise takeaways from Jensen Huang’s latest showcase.

Speed Without Guardrails: The Security Gap Enterprises Are Creating as They Scale AI Agents

As enterprises scale AI agents into autonomous participants in business processes, they're creating thousands of non-human identities — each with its own credentials, permissions, and access. While human users are closely monitored, trained, and governed, machine identities remain poorly inventoried, rarely rotated, and increasingly targeted.

Regulation Actioned: Inside Corlytics’ Approach to Responsible RegTech

Corlytics' Chief Data Officer Dr Oisin Boydell unpacks what AI-by-design means in practice for regulatory compliance — and why the hard calls must always stay with humans.

Why Integration — Not Data — Decides Whether Enterprise AI Scales

Historically, integration has been viewed as plumbing: essential but unglamorous middleware that connects applications and data sources. In the age of AI, this perception must change. Integration is no longer a background utility. It is the connective tissue that determines whether intelligence can flow across the organisation.

It’s Not the Model: Why Gender Bias in Enterprise AI Is a Human Problem

Four experts across AI ethics, insurance, media, and enterprise adoption go deep on how gender bias enters, compounds, and scales in enterprise AI — and why the real problem isn't in the data or the model, but in the human capability gaps, homogeneous teams, and uncritical adoption patterns surrounding them.

20 Women Taking On AI’s Hardest Problems

From governance and spatial intelligence to sovereign infrastructure and algorithmic justice — these are the women building, funding, auditing, and leading AI's most consequential work.

The Procedural Friction Eating Relationship Banking — and How AI Can End It

Relationship managers in commercial banking spend up to 60% of their time on administrative friction — not advising clients. AI's highest-value role isn't automating the relationship; it's eliminating the procedural clutter that's been eroding it for decades. But only if two foundations are in place: data lineage and explainability.

De-Risking the Crypto Portfolio: How AI Offers CFOs Control in a 24/7 Market

While the volatility of digital assets has long kept corporate finance at bay, artificial intelligence is introducing a new layer of continuous governance. Matic Jug explores how AI-driven risk control is finally making crypto a viable, manageable asset class for the enterprise.

6 Enterprise Tests to Expose Hidden AI Compliance Risks Across Borders

A step‑by‑step testing playbook to help IT leaders validate AI governance, data sovereignty and regulatory compliance worldwide.

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