training

No One Ever Failed a Tabletop. That Is the Problem.

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Traditional tabletop exercises in cybersecurity often fail to prepare teams for real breaches because they are static, predictable, and lack real consequences or dynamic adversary responses. Reflex Security's AI-driven simulations create adaptive, high-pressure scenarios that test decision-making in real time, providing detailed, evidence-based after-action reports that better align with regulatory requirements and improve incident response readiness.

https://cisoseries.com/no-one-ever-failed-a-tabletop-that-is-the-problem/

Why Your Most AI-savvy Employees Are Driving Shadow AI

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Employees most knowledgeable about AI often engage in using unauthorized AI tools at work to increase speed and overcome limitations of official systems, creating shadow AI challenges for CIOs. To manage this, organizations are rethinking governance and training strategies to balance encouraging experimentation with protecting data and maintaining oversight, emphasizing hands-on education that addresses technical, ethical, and security aspects while adapting AI tools to meet employee needs.

https://www.cio.com/article/4178359/why-your-most-ai-savvy-employees-are-driving-shadow-ai.html

The CIO’s Guide to Skills-Based Workforce Planning

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CIOs often find that while their organizations have sufficient IT staff, critical skills gaps—particularly in AI, cloud, and cybersecurity—hinder digital transformation efforts. Skills-based workforce planning addresses this by focusing on employees' specific capabilities rather than job titles, enabling greater workforce agility, better alignment with business priorities, and more effective talent deployment through continuous skills visibility, AI-assisted matching, and dynamic skill development programs. This approach helps organizations adapt rapidly to technological change, improving project success and business resilience.

https://www.techtarget.com/searchcio/tip/The-CIOs-guide-to-skills-based-workforce-planning

AI Training Platform for Teams

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TalentOS is an AI training platform designed to upskill teams by having them work on real business projects rather than generic coursework, providing measurable proof of AI skills through AI-graded outputs. It offers scalable pricing plans for teams of all sizes and emphasizes immediate, practical results to ensure AI adoption drives real business impact.

https://www.talentosapp.com/

Stop Blaming Your People: the Case for Human-Centred Cyber Security

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The article argues against blaming employees as the weakest link in cyber security and advocates for a human-centred approach that focuses on educating people as a key defense. Cyber security expert Caitriona Forde emphasizes shifting training from corporate obligation to teaching essential life skills that protect individuals and their families, thereby fostering a culture of empowerment rather than shame. With evolving AI threats, businesses must adopt practical measures like explaining risks, encouraging cautious behavior, sharing experiences openly, verifying requests, and governing AI use to build resilience and reduce incidents.

https://www.businessnews.com.au/article/Stop-blaming-your-people-the-case-for-human-centred-cyber-security

You Can’t Train Your Way Out of the AI Skills Gap

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Jeff Carson argues that while many enterprises recognize an AI skills gap and invest heavily in training, the core challenge lies not in skill deficiencies but in outdated work design. He emphasizes that true AI-driven transformation requires redesigning workflows, roles, and operating models to leverage AI’s capabilities effectively, moving beyond faster individual productivity to achieve improved organizational performance. CIOs play a critical role in leading this redesign to ensure that AI adoption translates into faster decisions, reduced bottlenecks, and better business outcomes.

https://www.cio.com/article/4165040/you-cant-train-your-way-out-of-the-ai-skills-gap.html

Why It’s Time to Stop Blaming Staff for Breaches

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Security awareness training has been widely adopted by companies but has not significantly reduced breaches, largely because it fails to keep pace with sophisticated, AI-driven, personalized phishing attacks. Experts argue that technology must do more to block threats before reaching employees, and training should be targeted, relevant, and supported by a positive security culture that encourages reporting mistakes rather than punishing them.

https://www.itweb.co.za/article/why-its-time-to-stop-blaming-staff-for-breaches/wbrpOqg2lYnMDLZn

Why Hiring ‘AI Engineers’ Won’t Work

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The article argues that the role of an “AI engineer” is a myth because AI work encompasses diverse functions requiring different skills and mindsets. It outlines three essential AI engineering archetypes—prototypers, builders, and scalers—each focusing on distinct phases from rapid experimentation to production scaling, and emphasizes the need for companies to hire and assess talent based on these specific roles rather than expecting a single person to cover all AI responsibilities. This nuanced understanding is crucial for enterprises to build effective AI teams and avoid costly mismatches.

https://www.cio.com/article/4162080/why-hiring-ai-engineers-wont-work.html

Beyond Awareness: Human Risk Management Metrics for CISOs

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Traditional cybersecurity awareness training often fails to sufficiently protect organizations against increasingly sophisticated human-targeted cyber threats. Forrester Research advocates for a human risk management approach that leverages behavioral data to identify and mitigate risky employee actions through targeted interventions, fostering a security culture focused on measurable behavior change rather than mere training completion. This data-driven strategy enables CISOs to align security metrics with business goals and improve overall cybersecurity posture by addressing the root causes of human vulnerabilities.

https://www.techtarget.com/searchsecurity/tip/Beyond-awareness-Human-risk-management-metrics-for-CISOs

AI Isn’t Failing, People Are Failing With AI

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The article emphasizes that AI failures stem from improper application rather than from the technology itself, highlighting the importance of domain expertise and understanding model operations. It distinguishes between the effectiveness of models like BERT and GPT, advocating for a risk-based framework in deploying AI to manage industry-specific challenges and data utilization. Successful AI transformation relies on organizational fluency with technology and strategic planning.

https://www.cio.com/article/4135361/ai-isnt-failing-people-are-failing-with-ai.html

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