
AI dependency is the next cyber resilience risk
AI dependency is creating hidden concentration risk as organisations rely on shared models, cloud platforms and infrastructure, making resilience, optionality and exit planning increasingly critical.

AI dependency is creating hidden concentration risk as organisations rely on shared models, cloud platforms and infrastructure, making resilience, optionality and exit planning increasingly critical.

Digital identity is evolving under EUDI regulation. Businesses must bridge centralised and decentralised systems while maintaining trust, security and seamless user verification across platforms.

Quantum computing is approaching real-world impact. Its benefits and risks will depend on policy, access, and governance decisions made by industry, government, and researchers today.

Biometrics face growing risk in the AI era as deepfakes rise, pushing organisations towards zero-knowledge architectures to protect identities and eliminate centralised data vulnerabilities critical.

AI agents are transforming software development, shifting developers from coders to orchestrators of intelligent workflows, where data, infrastructure and strategic oversight define success.

Edge computing strengthens cloud resilience by ensuring uptime during outages, enabling hybrid infrastructure strategies that protect critical workloads, reduce disruption, and support reliable business continuity.

How Formula 1’s AI-driven operations offer a blueprint for automotive manufacturers to improve agility, streamline workflows, and scale innovation across the entire vehicle lifecycle.

AI growth is driving energy demand sharply higher. Smaller, optimised models offer a sustainable path forward, reducing costs while maintaining performance and enabling wider enterprise adoption.

A practical AI maturity model helping procurement teams reduce backlogs, automate workflows, and evolve into strategic value creators delivering measurable ROI and business impact.

Inefficient security workflows are driving developer burnout, reducing productivity and increasing risk. Learn how automation and culture shifts can help teams regain focus and improve security outcomes.

AI in retail has moved from experimentation to execution, with success now defined by measurable outcomes, operational performance and real-world impact across supply chains.

Business resilience is often misunderstood. Discover the five maturity stages and how organisations can benchmark, strengthen operations, and move from reactive to strategically resilient.

AI performance is no longer driven by scale alone. Organised, connected context through knowledge graphs is emerging as the key to accurate, reliable enterprise intelligence.

Shadow AI is already embedded across organisations, creating unseen risks. Effective governance, visibility and control are now essential to manage AI adoption securely and responsibly.

Agentic AI is transforming enterprise operations, evolving from reactive co-pilots to proactive digital colleagues that drive autonomous outcomes, orchestration, and scalable business value.

AI-powered BPS is shifting from cost control to strategic advantage, enabling organisations to embed intelligence, improve decision-making, and drive long-term competitive growth.

Hybrid IT environments create major data visibility gaps. Organisations must prioritise unified data security, AI-driven detection and Zero Trust to protect sensitive data across complex ecosystems.

Lakshmi Hanspal of DigiCert explains how organisations can adapt to 47-day TLS certificate lifetimes by improving visibility, automating renewals and building crypto-agility.

AI does not scale through better code or tools. It scales through operating models, governance and alignment that allow organisations to embed autonomy safely and effectively.

AI hesitation is creating forward-looking technical debt. Adam Spearing of ServiceNow warns delayed system readiness will widen capability gaps and undermine enterprise competitiveness.

AI in retail delivers the greatest value behind the scenes, transforming supply chains with predictive insights, improving forecasting accuracy, reducing waste and enabling smarter operational decisions.

AI success depends on strong processes, clear outcomes and confident teams. Organisations that align people, workflows and data are far more likely to realise real AI value.

As AI natives enter the workforce, organisations must rethink governance, mentoring and productivity to bridge expectation gaps and embed intelligent systems responsibly.

Enterprise AI is moving beyond hype, shifting towards proactive systems, embedded intelligence and specialised models that deliver measurable impact, governance and real operational value.

AI must deliver measurable value in daily operations. From manufacturing to retail, businesses are shifting from pilots to practical deployment, building trust and preparing for agentic AI.

How telecoms solutions giant ALE is using its own experiences to help businesses across the world.

Inside the digital transformation of The Federal Home Loan Bank of Chicago.

Nathalie Marcotte, Helenio Gilabert and their team explain how Schneider Electric is adopting new technologies and business models to lead the market’s sustainability and efficiency efforts.

This month, Ben and Rom are joined by Drata’s co-founder and CEO Adam Markowitz. They discuss Adam’s past career as a rocket scientist, Drata’s influence on the SaaS market, and the secrets to his entrepreneurial success. Ben and Rom also review our case study on Ericsson.

Organisations across manufacturing, cybersecurity, finance, tax, retail and hospitality are turning AI pilots into measurable value through trusted data, governance and human judgement at scale.

Digital identity startup Incode is one of technology’s newest unicorns

How invisible digital infrastructure, composable architecture, and omnichannel delivery are reshaping storytelling, enabling publishers and media brands to deliver seamless audience experiences globally.

Digital identity is evolving under EUDI regulation. Businesses must bridge centralised and decentralised systems while maintaining trust, security and seamless user verification across platforms.

Quantum computing is approaching real-world impact. Its benefits and risks will depend on policy, access, and governance decisions made by industry, government, and researchers today.

Biometrics face growing risk in the AI era as deepfakes rise, pushing organisations towards zero-knowledge architectures to protect identities and eliminate centralised data vulnerabilities critical.

AI agents are transforming software development, shifting developers from coders to orchestrators of intelligent workflows, where data, infrastructure and strategic oversight define success.

Edge computing strengthens cloud resilience by ensuring uptime during outages, enabling hybrid infrastructure strategies that protect critical workloads, reduce disruption, and support reliable business continuity.

How Formula 1’s AI-driven operations offer a blueprint for automotive manufacturers to improve agility, streamline workflows, and scale innovation across the entire vehicle lifecycle.

AI growth is driving energy demand sharply higher. Smaller, optimised models offer a sustainable path forward, reducing costs while maintaining performance and enabling wider enterprise adoption.

A practical AI maturity model helping procurement teams reduce backlogs, automate workflows, and evolve into strategic value creators delivering measurable ROI and business impact.

Inefficient security workflows are driving developer burnout, reducing productivity and increasing risk. Learn how automation and culture shifts can help teams regain focus and improve security outcomes.

AI in retail has moved from experimentation to execution, with success now defined by measurable outcomes, operational performance and real-world impact across supply chains.

Business resilience is often misunderstood. Discover the five maturity stages and how organisations can benchmark, strengthen operations, and move from reactive to strategically resilient.

AI performance is no longer driven by scale alone. Organised, connected context through knowledge graphs is emerging as the key to accurate, reliable enterprise intelligence.

Shadow AI is already embedded across organisations, creating unseen risks. Effective governance, visibility and control are now essential to manage AI adoption securely and responsibly.

Agentic AI is transforming enterprise operations, evolving from reactive co-pilots to proactive digital colleagues that drive autonomous outcomes, orchestration, and scalable business value.

AI-powered BPS is shifting from cost control to strategic advantage, enabling organisations to embed intelligence, improve decision-making, and drive long-term competitive growth.

Hybrid IT environments create major data visibility gaps. Organisations must prioritise unified data security, AI-driven detection and Zero Trust to protect sensitive data across complex ecosystems.

Lakshmi Hanspal of DigiCert explains how organisations can adapt to 47-day TLS certificate lifetimes by improving visibility, automating renewals and building crypto-agility.

AI does not scale through better code or tools. It scales through operating models, governance and alignment that allow organisations to embed autonomy safely and effectively.

AI hesitation is creating forward-looking technical debt. Adam Spearing of ServiceNow warns delayed system readiness will widen capability gaps and undermine enterprise competitiveness.

AI in retail delivers the greatest value behind the scenes, transforming supply chains with predictive insights, improving forecasting accuracy, reducing waste and enabling smarter operational decisions.

AI success depends on strong processes, clear outcomes and confident teams. Organisations that align people, workflows and data are far more likely to realise real AI value.

As AI natives enter the workforce, organisations must rethink governance, mentoring and productivity to bridge expectation gaps and embed intelligent systems responsibly.

Enterprise AI is moving beyond hype, shifting towards proactive systems, embedded intelligence and specialised models that deliver measurable impact, governance and real operational value.