AI

Shadow AI ‘Double Agents’ Are Outpacing Security Visibility – and That’s a Serious Concern for UK Businesses

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UK businesses are rapidly adopting AI agents to automate tasks and boost productivity, with 62% already using them and 68% planning enterprise-wide rollouts soon. However, Microsoft’s Cyber Pulse report warns that these AI agents, acting autonomously across networks and systems, are outpacing security visibility and creating significant risks, highlighting the urgent need for robust governance, visibility, and zero trust security measures to manage and control their access safely.

https://www.techradar.com/pro/security/shadow-ai-double-agents-are-outpacing-security-visibility-and-thats-a-serious-concern-for-uk-businesses

CIO 100 Leadership Live Atlanta: AI Spending Enters a Reckoning Phase

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At the CIO 100 Leadership Live conference in Atlanta, technology leaders discussed a shift in enterprise AI from rapid growth to a phase emphasizing governance, data accountability, and business justification. Key themes included the need for evolved leadership skills beyond technical expertise, challenges in moving AI initiatives beyond proof of concept, the critical role of knowledge management and data governance, and the importance of integrating AI as a strategic, multidisciplinary leadership priority.

https://www.cio.com/article/4148267/cio-100-leadership-live-atlanta-ai-spending-enters-a-reckoning-phase.html

EnshittifAIcation

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In the article “EnshittifAIcation,” Stefano Marinelli describes challenges he faces dealing with AI-driven customer service bots and automated systems in managing e-commerce servers, highlighting issues such as rigid AI responses, misunderstandings about technical configurations, and inaccurate recommendations that ignore expert human input. He argues that overreliance on AI systems without proper human oversight leads to inefficiencies, confusion, and erosion of reliability, emphasizing that current AI lacks the ability to learn or understand context like experienced professionals do.

https://it-notes.dragas.net/2026/03/20/enshittifaication/

The Importance of Behavioral Analytics in AI-Enabled Cyber Attacks

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AI-enabled cyber attacks are evolving to use automation and mimic legitimate user behavior, enabling cybercriminals to conduct highly personalized phishing, credential abuse, and adaptive malware attacks that bypass traditional security models. To counter these threats, behavioral analytics must advance into dynamic, context-aware identity-based risk modeling that continuously monitors user activities across the entire security stack, enabling real-time detection of subtle anomalies and privilege misuse in hybrid and multi-cloud environments.

https://thehackernews.com/2026/03/the-importance-of-behavioral-analytics.html

Companies Know AI Is Essential for Cyber Defense but Aren’t yet Seeing Returns

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A new EY survey reveals that while nearly all cybersecurity leaders see AI as essential for defense and are deploying it, most have yet to realize significant returns from agentic AI security tools. The survey highlights companies' progress in adopting AI governance frameworks but notes that full integration into corporate culture is limited, stressing the need for robust governance and human oversight to maximize AI’s benefits and manage risks effectively.

https://www.cybersecuritydive.com/news/cybersecurity-ai-agentic-governance-ey-survey/815311/

We Asked Experts About the Most Responsible Ways to Use AI Tools – Here’s What They Said

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Three years after ChatGPT's release, AI use divides people into those who refuse it and those who use it daily. Experts advise using AI as a brainstorming partner, research assistant, and organizer while maintaining personal judgment, cautioning against overreliance and emphasizing the need to verify AI-generated information with credible sources.

https://www.theguardian.com/lifeandstyle/ng-interactive/2026/mar/18/how-to-use-ai-tools-expert-guide

Shadow AI Has Already Moved Into Your Organization

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The article explains that “shadow AI” is already widespread in organizations, as employees use public or unapproved AI tools to speed up work without going through IT or security review. Because these tools can be accessed instantly in a browser, blocking them is often ineffective, resulting in lost visibility into how company data is used. The article concludes that organizations must shift from trying to prohibit AI use to creating governance frameworks, approved tools, and clear policies that enable productivity while maintaining security and compliance. 

https://www.forbes.com/sites/tonybradley/2026/03/19/shadow-ai-has-already-moved-into-your-organization/

What It Takes to Level up Your Org’s AI Maturity

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In an interview with AI transformation practitioners Afshean Talasaz and Zar Toolan, key insights are shared on how organizations can advance their AI maturity from initial adoption to driving significant business impact. They emphasize the importance of a combined innovator-operator leadership mindset, detailed preparation, and aligning AI investments with long-term business strategies, supported by strong C-suite and CEO commitment. This approach helps companies move beyond treating AI as an operational tool to embedding it as a strategic asset that delivers measurable value and competitive advantage.

https://www.cio.com/article/4146645/what-it-takes-to-level-up-your-orgs-ai-maturity.html

AI Without Sovereignty Is Just Outsourced Intelligence

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In his opinion piece, Floyd DCosta argues that enterprises adopting AI often gain capability but lack sovereignty—control over how AI models and data are used—creating long-term risks and dependencies on third-party vendors. He emphasizes AI sovereignty as essential, encompassing governance, transparency, data and model control, operational autonomy, and strategic independence, warning that without it, organizations may inadvertently cede their competitive intelligence and face regulatory and operational challenges.

https://www.cio.com/article/4147102/ai-without-sovereignty-is-just-outsourced-intelligence.html

Deterministic AI: What It Is and When to Use It

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Deterministic AI refers to systems that produce the same output every time they receive the same input, combining AI’s ability to interpret data with deterministic workflows that ensure consistency and control. This hybrid approach uses probabilistic AI models to analyze and classify inputs while embedding their outputs in rule-based automation that executes reliably, making it ideal for enterprise workflows needing predictable, repeatable results. Zapier exemplifies this by orchestrating AI-powered workflows that maintain deterministic execution, blending AI’s flexibility in understanding complexity with automation’s dependability.

https://zapier.com/blog/deterministic-ai/

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