Why Most Enterprise AI Projects Fail Before They Scale
The hardest part is rarely the model. It is the operating system around it: ownership, workflow design, adoption and control.
Read the cover story →Issue 01 · Summer 2026
Understanding how AI reshapes work.
Independent analysis for executives, HR leaders and technology decision-makers.
Latest analysis
For leaders making consequential decisions.
Practical perspectives on implementation, governance, workforce change and cyber risk.
NEW
Enterprise AI Agents Need Context, Not Just Data
A partner-backed industry survey, recruiting data and emerging security research point to a practical lesson: trustworthy AI agents need organizational knowledge, clear controls and evidence of real-world performance.
01
Seven Tests for an Enterprise-Ready AI Agent Demo
A polished demo proves that an agent can act. It does not prove that an enterprise should trust it to act repeatedly, safely and economically.
02
The AI Skills Gap Is Really a Work Design Gap
Training people to use an AI tool is useful. Redesigning the work around it is what creates an organisational capability.
03
World Models: Why Spatial Intelligence Deserves Executive Attention
Language models changed how machines work with words. World models aim to help them represent, generate and interact with space.
04
AI Will Transform Recruitment — But Not in the Way Most People Expect
The real disruption is the redesign of the workflow and a new standard for human accountability.
05
Cybersecurity in the Age of AI Agents
As AI gains access to tools and workflows, the central question becomes what an agent is allowed to do.
06
Measuring AI ROI Beyond Productivity
Time saved is easy to announce and difficult to bank.
07
Five Questions Ai4 2026 Must Answer
The useful conversations will move beyond demonstrations and confront implementation.
Research notes
Short reads for fast-moving questions.
When productivity gains do not become financial gains
Efficiency has to be converted into capacity, cost reduction, quality or risk improvement.
Why human oversight fails when it is undefined
Oversight is an operating mechanism, not a sentence in a policy.
The hidden cost of fragmented AI tooling
Local experimentation can create enterprise-wide complexity.
Editorial desks
Six lenses on organisational change.
Enterprise AIImplementation, ROI, agents and operating models.Future of WorkJobs, skills, workflow redesign and workforce adoption.CybersecurityIdentity, control, resilience and AI-enabled threats.LeadershipDecision-making, accountability and change management.Research NotesShort, evidence-led analysis of emerging developments.Conference DeskPreviews, interviews, dispatches and post-event reports.
AI4 Las Vegas · 4–6 August 2026
Coverage built around implementation.
Enterprise ROI, agent governance, workforce redesign and cybersecurity through a European business lens.
Daily reportsConcise analytical dispatches.
Executive interviewsPractical questions on adoption and trust.
Keynote analysisWhat announcements mean for operators.
After-action reportA synthesis for European leaders.