AI

Managing the New Blend of Human and Virtual “Co-Workers”

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HR leaders must adapt to a workplace increasingly comprising human and AI collaboration. Key trends identified by Gartner for 2026 include challenges like layoffs due to anticipated AI productivity that hasn’t been realized yet, the need to protect employee mental well-being in the AI landscape, and managing “workslop” caused by poor-quality AI outputs. Additionally, there’s a focus on improving recruiting methods to combat candidate fraud, addressing insider threats amid AI advancements, supporting transitions to trades from tech roles, and ensuring processes are optimized by creative thinkers, not just tech experts. Lastly, employees may demand compensation for training AI counterparts modeled after themselves.

https://www.latimes.com/b2b/human-resources/story/2026-02-22/2026-future-of-work-trends-hr-leaders

Half the AI Agent Market Is One Category the Rest Is Wide Open

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Software engineering comprises nearly 50% of AI agent tool usage, while healthcare, legal, and other sectors each hold less than 5%, indicating vast untapped opportunities. Despite AI's capability to perform efficiently, user trust limits its deployment. Founders should focus on vertical-specific AI solutions, capitalizing on unique workflows and driving change management to unlock growth potential. There are approximately 300 vertical AI unicorns waiting to be created across various industries.

https://garryslist.org/posts/half-the-ai-agent-market-is-one-category-the-rest-is-wide-open

Stop Thinking of AI as a Coworker. It’s an Exoskeleton.

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AI should be viewed as an exoskeleton that enhances human capabilities, rather than as an autonomous agent. Companies that use AI to amplify human work achieve better results than those that expect autonomy. Exoskeleton examples demonstrate significant benefits across manufacturing, the military, and healthcare by reducing injuries and improving efficiency. In product development, AI tools like Kasava provide depth of analysis while keeping human judgment central. The future of AI lies in systems that integrate closely with human workflows, amplifying productivity rather than operating independently.

https://www.kasava.dev/blog/ai-as-exoskeleton

The Work Moved: What the AI Coding Debate Actually Agrees On

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AI coding has increased productivity (98% more PRs) but prolonged review times (91% longer), shifting work from coding to review processes. Various perspectives agree on data yet disagree on implications. Challenges include comprehension debt and the need for robust infrastructure. Strategies vary from spec-driven development to autopilot modes, focusing on context management and oversight. Risks involve reliance on AI without proper guardrails leading to misunderstandings and accountability issues. Ultimately, it's crucial to understand where complexity resides and ensure humans remain engaged in essential tasks.

https://leadership.garden/ai-the-work-moved/

An AI CEO Finally Said Something Honest : r/ExperiencedDevs

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Dax Raad, CEO of anoma.ly, candidly critiques the current state of AI in organizations, stating that teams lack good ideas, workers are unmotivated, and AI is used to reduce effort rather than increase efficiency. He warns that bureaucratic hurdles persist, and high costs of LLM bills are a growing concern for CFOs.

https://www.reddit.com/r/ExperiencedDevs/comments/1r6olcv/an_ai_ceo_finally_said_something_honest/

AI Is Spreading Faster Than Companies Can Secure It, CISO Survey Finds

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AI adoption is outpacing security measures, per a Pentera survey of 300 U.S. CISOs. Key findings: 67% lack visibility into AI usage, 44% report lagging AI security, and major challenges include expertise shortages and reliance on outdated security controls. Despite funding for AI security, it lacks dedicated budgets, highlighting significant gaps in securing evolving AI systems amidst complex IT environments.

https://www.prnewswire.com/il/news-releases/ai-is-spreading-faster-than-companies-can-secure-it-ciso-survey-finds-302691361.html

When AI Agents Pay: Who Owns the Compliance Liability?

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AI agents in commerce raise complex compliance issues regarding transactional liability. With their adoption accelerating, traditional regulatory frameworks (such as PCI DSS, AML, and DORA) may struggle to keep pace, as compliance is hard to assign when AIs initiate payments. Financial institutions must proactively assess their compliance strategies for AI interactions to avoid future liability risks, particularly around transaction monitoring, script security, and operational resilience. Immediate steps include mapping integrations and recalibrating AML systems. Delayed action may lead to regulatory crises as compliance standards evolve.

https://www.finextra.com/blogposting/30917/when-ai-agents-pay-who-owns-the-compliance-liability

From Innovation to Regulation: How Internal Audit Must Respond to the EU AI Act

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The EU AI Act, a global standard for AI regulation, requires organizations worldwide to address AI risks through governance, controls, and accountability. Internal auditors must adapt to this shift, auditing AI governance, risk classification, data quality, human oversight, and third-party AI risk to ensure compliance.

https://www.wolterskluwer.com/en/expert-insights/innovation-regulation-how-internal-audit-must-respond-eu-ai-act

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