How State CIOs Are Using GenAI

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82% of state CIOs report employees use generative AI daily, up from 53% in 2024. Most adopt a low-risk strategy: pilot projects (90%), proofs of concept (86%), and employee training (71%). Only 25% have dedicated AI funding. AI aids workplace efficiency and service delivery, with usage for internal tasks and some exploration of public-facing services. CIOs support federal AI regulations while opposing restrictive moratoriums.

https://www.smartcitiesdive.com/news/ai-state-cio-government-adoption/803978/

European Commission Publishes Draft Guidance on Reporting Serious AI Incidents

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EU Commission released draft guidance on reporting serious AI incidents under Article 73 of the EU AI Act, requiring high-risk AI system providers to notify authorities of serious incidents. Comments accepted until Nov 7, 2025; final guidance expected to apply from Aug 2, 2026. Key points include broad definitions of “serious incidents,” tight reporting timelines, and potential penalties for non-compliance. Companies must establish clear reporting processes to meet obligations and align with other regulatory requirements.

https://www.lw.com/en/insights/european-commission-publishes-draft-guidance-reporting-serious-ai-incidents

The 10 Biggest Issues CISOs and Cyber Teams Face Today

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Important topics for cybersecurity leaders include securing AI infrastructure, rising AI-enabled threats, budget constraints, and preparing employees against sophisticated scams. They face challenges with an expanding threat landscape, limited budgets, prioritizing tasks, risk management, and the emergence of quantum computing threats.

https://www.csoonline.com/article/4077442/the-10-biggest-issues-cisos-and-cyber-teams-face-today-2.html

Can Cybersecurity Withstand the New AI Era?

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The pace of technological change, especially in AI and quantum computing, is overwhelming existing cybersecurity measures and further exposing organizations to a shortage of skilled professionals. Small and medium enterprises, and those in underdeveloped regions, are especially vulnerable, lacking the resources for advanced protection. Plug-and-play, automated, and quantum-ready solutions are critical so that robust cybersecurity is no longer exclusive to well-funded enterprises. By democratizing access to smart security tools, organizations can better withstand accelerated cyber threats, maintaining business continuity and competitiveness. Proactive, accessible security must become a necessity rather than a luxury as risks accelerate at machine speed.

https://www.weforum.org/stories/2025/10/can-cybersecurity-withstand-new-ai-era/

Microsoft Sued for Allegedly Forcing M365 Users to Pay for AI

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Microsoft is being sued in Australia for allegedly misleading users of its Microsoft 365 subscriptions into paying for its AI assistant, Copilot, by not disclosing a cheaper, non-AI “Classic” plan. The ACCC claims Microsoft hid this option, leading to price increases for many users. The lawsuit seeks penalties and consumer redress for what is characterized as misleading conduct, including claims that accepting AI features or facing a price increase were mandatory.

https://cyberinsider.com/microsoft-sued-for-allegedly-forcing-m365-users-to-pay-for-ai/

10 Metrics to Track Enterprise AI Success

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CIOs face challenges in identifying valuable AI use cases amidst numerous options. Many struggle to demonstrate AI's value, risking overextension and project bloat. Effective implementation requires tracking specific metrics for improvement. Key metrics include average labor costs, working capital, supplier spending, and employee satisfaction scores. Defining success and aligning technical metrics to business outcomes is crucial for AI project success, as highlighted by Arun Chandrasekaran from Gartner at the IT Symposium/Xpo.

https://www.ciodive.com/news/top-metrics-track-enterprise-ai-success/803891/

Why IT Projects Still Fail

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The article highlights common reasons IT projects fail, such as poor project management, lack of alignment with business goals, insufficient resources, and inadequate change management. Effective engagement from business sponsors and stakeholders is crucial for success. The importance of skilled teams and project managers is emphasized to improve project outcomes.

https://www.cio.com/article/4077457/why-it-projects-still-fail-2.html

Europe Wrote the AI Rulebook. Can It Deliver on Its Ambitions?

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Europe's AI Act and Apply AI Strategy aim for values-based AI regulation and innovation, despite pressure from US tech companies to delay enforcement. Effective regulation is crucial for trust, investment security, and consumer protection. Europe’s technological and democratic sovereignty hinges on prioritizing public values over mere market convenience. The goal is a complementary AI Democracy Action plan to enhance governance and reduce dependency on US tech, affirming Europe's commitment to democratic digital sovereignty and fundamental rights.

https://www.techpolicy.press/europe-wrote-the-ai-rulebook-can-it-deliver-on-its-ambitions/

AI 2030: Preparing for the Age of Autonomous Cybercrime

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Check Point Software Technologies warns of an upcoming era of autonomous AI-driven cybercrime, where AI tools may execute sophisticated attacks with minimal human oversight. Key threats include machine-driven assaults, self-evolving malware, AI impersonation, and compromised supply chains. Organizations are advised to adopt security-first AI tools, implement zero trust principles, secure supply chains, and integrate automated security in development to combat these emerging challenges.

https://blog.checkpoint.com/executive-insights/ai-2030-the-coming-era-of-autonomous-cyber-crime/

Predicting Cyber Attacks Before They Happen

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AI is shifting cybersecurity from a reactive to a proactive approach by predicting cyberattacks before they happen. This enables anticipating and mitigating threats in advance.

  • Traditional cybersecurity tools are reactive and struggle against new or unknown threats.
  • Cyberattacks are becoming more complex, employing advanced, AI-driven tactics.

AI in Predictive Cybersecurity

  • Machine learning identifies threat patterns from vast data (e.g., phishing detection).
  • Real-time anomaly detection spots unusual behaviors instantly (e.g., odd logins, insider threats).
  • Predictive analytics uses historical data to forecast and simulate future attacks.
  • AI-powered platforms enable sharing threat intelligence across organizations.

Benefits

  • Moves defense from reactive to proactive, reducing risks and losses.
  • Processes data faster and more efficiently than human teams.
  • Continuously adapts to new threats, reducing human error.

Challenges

  • It can produce false positives that overwhelm security teams.
  • Raises data privacy concerns with large data requirements.
  • Relies on high-quality, unbiased data for accuracy.
  • Attackers may also use AI, leading to an ongoing arms race.

Future Outlook

  • AI systems may soon autonomously defend against threats in real time.
  • The line between proactive and real-time response is blurring as technology advances.

https://www.ibm.com/new/product-blog/ai-powered-threat-intelligence-predicting-cyber-attacks-before-they-happen

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