AI governance, AI risk, responsible use of automation and the controls needed when software starts making recommendations.
11 articles tagged AI on vesely.sk.
AI transparency will not be solved by a small icon under an image. Organisations will need provenance metadata, signatures, watermarking, verification tools, human review and audit evidence.
Read article →AI can generate working applications quickly, but functionality is not the same as security. The next challenge is proving that AI-generated systems are hardened, compliant and trustworthy enough for production.
Read article →The future of AI will not be decided only by larger models or longer context windows. It will be decided by the engineering process around them: workflow, memory, rules, verification, review and evidence.
Read article →Vibe coding is fast, but without durable memory, reusable skills, deterministic verification and independent review, AI-assisted development can quickly become chaos.
Read article →AI makes it easier than ever to build and deploy software. That also means basic web security, AppSec and DevSecOps checks must happen before publishing, not after deployment.
Read article →Autonomous AI agents change enterprise security assumptions. The next generation of cybersecurity will be about continuously proving that infrastructure is still trustworthy.
Read article →NIS2, AI and modern infrastructure change risk management from a static register into a continuous evidence problem. Existing open-source tools solve parts of it, but the missing layer is proof of trust.
Read article →The future of AI will not be defined only by what systems can do, but by who can govern their risks, security, accountability and auditability.
Read article →When HR uses AI to screen, score or evaluate people, the question is not only whether it is useful, but whether it is legal, safe, fair and governed.
Read article →AML and KYC require customer due diligence, but they are not a blank cheque for uncontrolled data collection, AI scoring and permanent profiling.
Read article →Companies are adopting AI quickly, but the hard question is who can prove what tools are used, what data enters them, what decisions they influence and who is responsible.
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