AI

Briefing

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TLDR: The EU Artificial Intelligence (AI) Act 2024 establishes a regulatory framework for AI, promoting human-centric use while ensuring safety and ethical standards. It categorizes AI risks into four levels and restricts harmful applications. The Act mandates compliance from August 2026, with interim obligations starting February 2025, emphasizing AI literacy among HR professionals to mitigate risks. The legislation aims to foster trust and encourage responsible AI adoption, while requiring significant efforts in education and guidance for effective implementation.

https://www.cipd.org/ie/views-and-insights/thought-leadership/insight/implications-eu-ai-act/

How 100 Enterprise CIOs Are Building and Buying Gen AI in 2025

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TLDR Summary:
In 2025, enterprise AI spending exceeds expectations, becoming a permanent budget item driven by internal and customer-facing use cases. Enterprises increasingly utilize multiple AI models, with OpenAI, Google, and Anthropic leading the market. Procurement processes mirror traditional software buying, emphasizing cost and security. Enterprises are shifting from building to buying AI applications as the ecosystem matures, particularly in software development and customer support. However, concerns around outcome-based pricing persist. Overall, the landscape shows strategic deployment, diversified model use, and a shift towards AI-native applications.

https://a16z.com/ai-enterprise-2025/

EU AI Act Unpacked #25: European Commission Releases Critical AI Act Implementation Guidelines (Part 3)

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European Commission released guidelines on prohibited AI practices under the EU AI Act on February 4, 2024. These non-binding guidelines clarify interpretations and enforcement of Article 5's prohibitions, impacting developers and deployers of AI systems. Key prohibitions include:

  1. Predictive policing: AI cannot predict criminal behavior based on profiling or personality traits.
  2. Untargeted facial image scraping: Prohibits collecting facial data from the internet without targeting specific individuals.
  3. Emotion recognition in workplaces/education: Bans AI systems recognizing emotions in these contexts to prevent discrimination.

Exceptions exist for certain practices, but companies must ensure compliance to navigate the regulatory landscape.

https://www.lexology.com/library/detail.aspx?g=ef05513f-5e88-4614-86b4-659468de7f05

CIO Wants to Clone Top Techies as Digital Twin and AI Agents

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CIO Dr. Vince Kellen at UC San Diego plans to enhance tech staff productivity by creating digital twins and AI agents to automate repetitive tasks. He aims to address funding pressures and security challenges through automation, enabling his team to focus on complex threats. Kellen proposes digitizing expert knowledge to improve AI's network management and reduce IT professionals' after-hours work.

https://www.theregister.com/2025/06/12/cio_wants_to_grow_tech/

Support for AI Act Pause Grows but Parameters Still Unclear

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Support for delaying parts of the EU's AI Act is increasing, following a meeting of member states and the European Commission's tech leaders. They propose a “stop the clock” approach due to impending deadlines and unresolved guidelines. Member states differ on how long to postpone implementations, with calls for up to two years for some components. The AI industry endorses this delay, citing the need for additional time for compliance. However, any amendments would require legislative review, and predictions on outcomes are uncertain, highlighting divisions within the Commission.

https://iapp.org/news/a/support-for-ai-act-pause-grows-but-parameters-still-unclear

The Enterprise Is Not Ready for Vibe Coding — Yet

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Vibe coding, using AI for software development, intrigues businesses but isn’t yet ready for widespread implementation due to security and scalability issues. Experts advocate for cautious adoption, recommending controlled experiments while acknowledging the need for engineers to upskill. By 2028, Gartner predicts that vibe coding will generate 40% of new software, but organizations must ensure rigorous standards to mitigate risks.

https://www.ciodive.com/news/vibe-coding-enterprise-CIO-strategy/750349/

Will AI Replace Cybersecurity? Not Quite—But It’s Rewriting The Rules

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AI is transforming the cybersecurity landscape, shifting the battle to AI versus AI, where cybercriminals leverage advanced technologies for larger-scale attacks. This evolution raises concerns about the vulnerabilities of businesses reliant on AI for operations. Cyber criminals can exploit these systems, causing disruptions and financial damage. To counter this, cybersecurity firms are employing AI-based defensive technologies to proactively protect against threats. The future of cyber warfare hinges on using AI as both a tool for defense and a weapon for attackers.

https://www.forbes.com/sites/michaelashley/2025/05/30/will-ai-replace-cybersecurity-not-quite-but-its-rewriting-the-rules/

AI Literacy – The Commission’s Pointers on Building Your Programme

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EU AI Act mandates AI literacy for providers and users of AI systems since February 2025. Compliance expectations are vague, emphasizing staff training to understand AI risks and legal implications. All stakeholders, including contractors and clients, must be educated on AI. Tailored approaches are required, particularly for high-risk systems. No universal standards exist; training is context-specific. Non-compliance may lead to enforcement from August 2026, but exact penalties are unclear. Effective AI literacy is essential for sound AI governance, regardless of direct AI Act applicability.

https://www.dataprotectionreport.com/2025/05/ai-literacy-the-commissions-pointers-on-building-your-programme/

Global Cybersecurity Agencies Release AI Data Security Guidelines, Highlight Data Integrity as Weakness

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Global cybersecurity agencies, led by CISA and partnered with NSA and FBI, issued guidelines on securing AI data, noting data integrity as a vulnerability. The guidelines stress the importance of robust data protection throughout the AI lifecycle, offering best practices for risk management, data provenance, and continuous assessments. They highlight that compromised data can lead to flawed AI outputs and emphasize the necessity of strong encryption and access controls for safeguarding sensitive information. The goal is to enhance awareness and resilience against evolving cybersecurity threats, ensuring trustworthiness in AI systems.

https://industrialcyber.co/threats-attacks/global-cybersecurity-agencies-release-ai-data-security-guidelines-highlight-data-integrity-as-ais-weakness/

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