productivity

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recognize an AI skills gap and invest heavily in training, the core challenge lies not in skill deficiencies but in outdated work design.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

The Best AI Employees Don’t Use It for Speed—They Use It to Think, Study Finds

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A study by KPMG and the University of Texas analyzed over a million AI interactions among thousands of employees, finding that the most effective AI users treat the technology as an intellectual partner for complex tasks rather than just a tool for speeding up simple work. These top employees iteratively refine AI prompts and set clear boundaries to guide responses, highlighting that only about 5% of users demonstrate such sophisticated AI habits, which companies can foster through deliberate training and structured AI tool deployment.

https://www.inc.com/kit-eaton/the-best-ai-employees-dont-use-it-for-speed-they-use-it-to-think-study-finds/91339051

A.I. Should Elevate Your Thinking, Not Replace It

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The article discusses how AI in software engineering can either elevate an engineer’s thinking by removing tedious tasks and enabling deeper problem-solving or lead to “outsourced thinking,” where individuals rely on AI-generated answers without true understanding, risking long-term competence. It emphasizes that valuable engineers use AI to enhance judgment and create new knowledge, while early-career engineers, in particular, must engage with foundational challenges to develop critical skills. It also warns that organizations and leaders must distinguish genuine technical depth from superficial fluency to maintain engineering quality and innovation.

https://www.koshyjohn.com/blog/ai-should-elevate-your-thinking-not-replace-it/

Microsoft Copilot Cheat Sheet: a Complete Guide to Microsoft’s AI

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Microsoft Copilot is an AI-powered assistant integrated across Windows, Edge, Microsoft 365, and Teams, designed to help users by drafting emails, summarizing meetings, creating presentations, and automating tasks via natural language prompts using advanced AI models like OpenAI’s GPT-5 and Anthropic’s Claude. Its key 2026 features include the agentic Cowork mode for multi-step task execution within Microsoft apps, voice interaction, 3D modeling, and deeper contextual awareness through Work IQ. While Copilot is deeply embedded in Microsoft’s ecosystem and valuable for enterprise users already invested in Microsoft 365, it faces criticism regarding output consistency, ecosystem lock-in, and limitations compared to specialized AI tools.

https://www.eweek.com/news/microsoft-copilot-cheat-sheet-complete-guide-2026/

The AI Trap: Faster Solution, Same Problem

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In “The AI trap: Faster solution, same problem,” David Angelow explains that despite widespread AI adoption, many organizations see no measurable productivity gains because they automate existing complex or inefficient processes without simplifying them first. He argues that the key to AI delivering real value lies in redesigning and streamlining workflows before automation, emphasizing the long-standing principle that technology should accelerate well-designed processes rather than perpetuate waste.

https://www.cio.com/article/4154559/the-ai-trap-faster-solution-same-problem.html

What CIOs Are Most Looking to Replace with AI Today

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A 2026 survey of 141 CIOs reveals that customer service management (26%), finance operations (21%), and project management (20%) are the software categories most prone to AI-driven vendor replacement, driven by AI’s ability to streamline coordination and workflow visibility. Meanwhile, 54% of CIOs are pursuing vendor consolidation, with 45% of AI budgets replacing existing software spend, signaling a shift where AI adoption often comes at the expense of traditional tools, although deeply integrated platforms like ERP and general productivity suites remain relatively protected due to high switching costs.

https://www.saastr.com/cioreplaceai/

How to Be Less Busy and More Effective in Cyber

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The article discusses how cybersecurity professionals often mistake busyness for effectiveness, highlighting a new framework inspired by MITRE ATT&CK that identifies common unproductive patterns like excessive meetings and fragmented attention that degrade performance. Experts emphasize focusing on meaningful outcomes rather than activities, managing work-life boundaries, and regularly assessing tasks and meetings to improve both security posture and personal well-being.

https://cisoseries.com/how-to-be-less-busy-and-more-effective-in-cyber/

We Asked Experts About the Most Responsible Ways to Use AI Tools – Here’s What They Said

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Three years after ChatGPT's release, AI use divides people into those who refuse it and those who use it daily. Experts advise using AI as a brainstorming partner, research assistant, and organizer while maintaining personal judgment, cautioning against overreliance and emphasizing the need to verify AI-generated information with credible sources.

https://www.theguardian.com/lifeandstyle/ng-interactive/2026/mar/18/how-to-use-ai-tools-expert-guide

AI Still Doesn’t Work Very Well, Businesses Are Faking It, and a Reckoning Is Coming

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Experts from AI advisory firm Codestrap warn that enterprise AI applications often fail to deliver expected benefits due to underlying model limitations and lack of proper metrics to assess AI-generated code quality and business content. They predict a reckoning in 8-9 months as AI misuse leads to failures, lawsuits, pricing pressures, and insurance challenges, urging businesses to adopt clearer strategies, measure true outcomes, and address the hype around AI capabilities.

https://www.theregister.com/2026/03/17/ai_businesses_faking_it_reckoning_coming_codestrap/

Every Layer of Review Makes You 10x Slower

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The article argues that each additional layer of review in a process slows progress by a factor of ten, primarily due to waiting time rather than effort, and this bottleneck is not alleviated by AI coding tools. While reviews are necessary to maintain quality and reduce costly mistakes as organizations grow, excessive layers can degrade efficiency and mask root causes of problems, leading to a culture that values checks over genuine quality improvement. The author suggests adopting a Deming-inspired approach emphasizing trust, continuous systemic improvements, and modular small teams that produce high-quality components to reduce reliance on slow review cycles and create a more effective, scalable engineering culture.

https://apenwarr.ca/log/20260316

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