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.
What is critical thinking?
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.”
AI has elevated the importance of critical thinking. We don’t want people to accept AI’s responses and actions as absolute truths, and we do want them to continue developing their analytic and creative skill sets. While critical thinking is a concept many understand intuitively, leaders must provide employees with clear, tangible ways to apply it in their work.
Noelle Federico, CEO at Fortunato Partners, adds, “The goal is not to have everyone think the same way; it is to create an environment in which people challenge assumptions, consider different perspectives, and contribute to better decisions.”
Business and IT leaders have been communicating the target behaviors of their cultures that drive innovation, resiliency, and collaboration for some time. Roll back to the early internet days, and many organizations shifted from command-and-control management approaches to agile ways of working and agile mindsets. Devops introduced new behaviors, including blameless postmortems and ownership of what you ship. Organizations promoted design thinking to empathize with the user’s context and to reframe problems before solving them.
In my conversations with experts, we discussed seven behaviors that drive critical thinking. Organizations should encourage these in their teams as they amplify talent in the AI era.
1. Lead with vision about AI
AI is driving a pace of change that challenges how leaders should engage employees on strategy and objectives. Becoming too prescriptive can lead to a narrow focus around short-term, productivity-driving objectives rather than targeting transformation opportunities.
“We can’t direct critical thinking; we need to inspire it,” says Jennifer Griffin Smith, chief market officer at Acquia. “AI will elevate your critical thinking if you lead with the vision of AI as a thought partner and the thing that makes us better at everything, not just what we do but the results we drive.”
Recommendation: Redesign your organization’s vision statement template to capture AI strategic opportunities, define objectives for experiments, and consider a broader definition of business value.
2. Capture the problem statement
LLMs make it easy for teams to go from idea to answers too quickly. This behavior can drive teams to “chase rabbits” by pursuing non-essential work or building AI capabilities without defining the problem.
“To encourage critical thinking for any digital transformation initiative, leaders should challenge their team to truly understand the problem they’re trying to solve before technology ever enters the picture,” says Guy Yehiav, president at SmartSense by Digi. “The team should build the process and KPIs for success before ever engaging the technology, while leaders create a culture where teams are encouraged to explore new ideas, question assumptions,
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