productivity

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

Why Hasn’t AI Made Work Easier?

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Cal Newport discusses how, despite AI tools promising to ease work burdens, recent research shows they have actually intensified activity in many work tasks—particularly shallow ones like email and messaging—while decreasing time spent on focused, deep work. He warns this pattern mirrors past technological shifts where increased efficiency led to busier workflows without boosting high-value productivity.

https://calnewport.com/why-hasnt-ai-made-work-easier/

The “Last Mile” Problem Slowing AI Transformation

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The “Last Mile” Problem, the final hurdle in AI transformation, is preventing companies from scaling AI pilots into enterprise-wide operating models. Despite widespread adoption of AI tools, many organizations struggle to convert individual productivity gains into significant organizational value. This is due to structural frictions, including the proliferation of pilots, the productivity gap, process debt, and governance challenges in an agentic world.

https://hbr.org/2026/03/the-last-mile-problem-slowing-ai-transformation

When Using AI Leads to “Brain Fry”

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A study of 1,488 U.S. workers found that while AI can alleviate burnout by replacing repetitive tasks, it can also cause “AI brain fry,” a form of mental fatigue from excessive oversight of AI tools. This cognitive strain, characterized by difficulty focusing and slower decision-making, leads to increased errors and decision fatigue. The study highlights the need for thoughtful AI-driven workflows to mitigate these negative effects.

https://hbr.org/2026/03/when-using-ai-leads-to-brain-fry

CIO AI Priorities Pivot From Productivity to Innovation

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CIO AI priorities have shifted significantly, with a dramatic drop in focus on productivity (from 67.5% to 41.8%) and automation (from 69% to 54.1%), while emphasis on innovation and modernization nearly doubled to 32.4%. A majority of CIOs now report well-developed AI plans, marking a pivot from pilot testing to full-scale implementation. AI spending as a focus area doubled, particularly in R&D, as businesses seek transformative capabilities over efficiency. Cybersecurity priorities also declined.

https://futurumgroup.com/press-release/cio-ai-priorities-pivot-from-productivity-to-innovation/

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