Employees are increasingly using large language models (LLMs) and AI agents to get work done. Many are using agents to complete tasks, and others are using LLMs to generate content, vibe coding tools to develop applications, and agent orchestration platforms to automate workflows.
Employees are increasingly using large language models (LLMs) and AI agents to get work done. Many are using agents to complete tasks, and others are using LLMs to generate content, vibe coding tools to develop applications, and agent orchestration platforms to automate workflows.
According to Kyndryl’s People Readiness Report, while 57% of organizations have embedded AI into core processes or deployed AI broadly, only 23% believe their workforce is fully ready to use AI effectively. Kim Basile, CIO at Kyndryl, says, “Leaders must help employees understand how their work is changing, redesign roles and workflows around AI, and build workforce readiness through upskilling, retraining, and change management.”
Critical thinking is a key discipline for leaders to develop in their organizations, as AI increasingly handles tasks, creates content, and augments people’s skills.
There are many ways to define critical thinking. One research paper from 1987 defines it as an “intellectually disciplined process of actively and skillfully conceptualizing, applying, analyzing, synthesizing, and/or evaluating information.” A simpler definition is, “thinking in which you question, analyze, interpret, evaluate, and make a judgment about what you read, hear, say, or write.”
In the Coffee With Digital Trailblazers gatherings I host weekly on LinkedIn Live, critical thinking was identified as a top skill in the episode on reskilling mid-career leaders. In the World Economic Forum’s Future of Jobs report, employers list aspects of critical thinking, including analytical and creative thinking, as the most sought-after core skills.
“It’s critical for organizations to create an atmosphere where questioning assumptions is expected, diverse perspectives are welcomed, and decisions are based on evidence rather than hierarchy or intuition,” says Raluca Rusu, CEO of R Systems Europe. “Equally important is fostering psychological safety so people feel comfortable challenging ideas, admitting uncertainty, and learning from experimentation without fear of blame.”
In context
- Topic: Cloud y Arquitectura — Nube pública, híbrida, costos y decisiones de infraestructura.
- Source: InfoWorld
- Published: 14/10/2026
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Why it matters
After a few years, nearly every organisation that migrated discovers the same thing: the bill grows faster than the business. Not because the cloud is expensive, but because nobody switches off what is no longer used and nobody has the incentive to check.
What I look at in these announcements is portability. The more comfortable a platform is, the harder it usually is to leave, and that comfort gets paid for in negotiating power three years later, exactly when renewal comes up and there is no credible alternative left.
What usually goes wrong
What I see fail most is the literal migration. The system gets moved exactly as it was, nothing redesigned, and you end up paying hourly for what used to be paid once. It works the same, costs more, and two years later somebody asks why it was done. Lift and shift is not modernising.
What to watch
- Three-year total cost with real growth, not the first-year promotion.
- How hard it would be to leave or move a piece to another provider, which is future negotiating power.
- Who sees the bill and in what detail: with no owner for the spend, the spend grows on its own.
How I read this entry
What I would install alongside any move to the cloud is the discipline of switching things off. Tag everything by owner, review monthly what is running unused, and give somebody the authority to turn it off. Without that, waste eats the promised savings within two years.
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Living through this in your own team?
Open the chat and tell me how you're handling it. I'm interested in comparing notes.