TCS Global AI head Ashok Krish emphasizes AI drives skill transformation rather than job loss; sees it as a board-level priority for cultural and technological change. He notes AI can streamline workflows and reshape projects without eliminating jobs, generating new opportunities in various industries.
Rise of Responsible AI in 2025: Focus on ethics, regulation, and transparency in AI development. Businesses and governments collaborate on frameworks to enhance accountability and prevent misuse. Key issues include bias, data ethics, and AI explainability. Organizations adopt governance measures and prioritize ongoing monitoring. Ethical AI practices provide competitive advantages and foster trust. Collaboration across sectors is essential for establishing best practices in AI governance.
https://www.techiexpert.com/the-rise-of-responsible-ai-regulation-ethics-transparency-in-2025/
CISOs must adapt to evolving data protection regulations like DPDP and GDPR, incorporating compliance into security practices. Their roles now include interpreting laws, implementing technical safeguards (encryption, access controls), and ensuring data governance. Continuous monitoring, incident response, and collaboration with Data Protection Officers are essential for balancing security with regulatory demands. A risk-driven approach prioritizes security outcomes while maintaining compliance, requiring robust strategies and employee awareness in data handling.
Cybersecurity leaders must recognize that false confidence can lead to vulnerability. Organizations often misjudge their preparedness, relying on outdated beliefs and temporary compliance. To enhance cyber resilience, businesses should focus on continuous risk monitoring, effective incident response, and integrating security into all operations. Lessons from real-world breaches emphasize the need for vigilance, addressing unseen vulnerabilities, and securing supply chains. True resilience means embedding security into the organizational culture, prioritizing it at the highest levels, and empowering all employees to be proactive defenders against cyber threats.
GenAI in Networking: Prompt Engineering Insights
Effective GenAI usage in networking relies on crafting precise prompts. Specificity, context, examples, and structured queries enhance AI outputs. Engineers must understand compliance needs and refine prompts iteratively. GenAI can automate configurations, troubleshoot issues, and monitor performance, fostering human-AI collaboration while ensuring security and standards adherence.
https://www.techtarget.com/searchnetworking/tip/GenAI-prompt-engineering-tactics-for-network-pros
The EU AI Act, effective August 2026, requires organizations using AI in the EU to classify AI systems by risk, implement governance frameworks, ensure data quality, and maintain ongoing compliance to avoid fines of up to €35 million or 7% of global revenue. Businesses need to assess their AI systems, collaborate with compliance partners, and establish monitoring tools.
EU Commission establishes guidelines for prohibited AI practices under AI Act, effective February 2025. Prohibitions include harmful manipulation, exploitation of vulnerabilities, social scoring, predictive criminal assessments, untargeted facial data scraping, emotion recognition, biometric categorization, and real-time remote biometric identification. Guidelines aim to clarify compliance and foster uniform application of the Act across the EU, though they are non-binding. Providers and deployers are responsible for ensuring AI systems meet regulations.
EU's push to “simplify” tech regulation aims to streamline its complex laws, raising concerns about diluting hard-won protections like GDPR and the AI Act. Amid geopolitical competition with the US and China, 13 member states advocate for deregulation, arguing it hampers innovation. Experts warn this may benefit dominant tech firms rather than smaller businesses and stress the need for a coherent strategy rather than unfocused deregulation. Fragmentation and ineffective regulation hinder innovation in Europe, signaling that reform should focus on coordination and support for startups, not dismantling existing protections.
https://www.techpolicy.press/whats-behind-europes-push-to-simplify-tech-regulation/
EU Commission clarifies AI definition: The Commission published guidelines detailing the definition of AI systems under the AI Act, outlining seven components, including machine-based systems, autonomy, adaptability, objective-driven outputs, inference capability, environmental interaction, and influence over environments. The guidelines help companies assess AI Act applicability. However, the guidelines are non-binding and not yet formally adopted.
https://www.orrick.com/en/Insights/2025/04/EU-Commission-Clarifies-Definition-of-AI-Systems
Biometrics in the EU are regulated by the GDPR and the AI Act, which address the use of biometric technologies beyond security into areas like emotion recognition and employee monitoring. The GDPR governs the processing of biometric data as personal and, in some cases, “special category” data requiring consent. The AI Act categorizes biometric systems by risk, with real-time remote identification largely prohibited, and specific rules for emotion recognition and categorization. Organizations face complex compliance challenges due to overlapping regulations, requiring a nuanced understanding of technology and legal responsibilities.
https://iapp.org/news/a/biometrics-in-the-eu-navigating-the-gdpr-ai-act
