PMI, WSJ Study Puts Human Judgment at AI’s Center

Philip Morris International and WSJ Intelligence have released a new study examining how human cognition is changing as artificial intelligence becomes embedded in workplace workflows. Surveying more than 2,500 business professionals across five countries, The Cognition Index Research Report finds strong confidence in AI’s ability to improve decision-making, but also identifies human judgment, ethics, critical thinking and empathy as capabilities companies need to deliberately preserve.

The workplace AI debate has largely focused on productivity, automation and the future of jobs. A new research project from Philip Morris International (PMI) and WSJ Intelligence shifts the question toward something more fundamental: what happens to human judgment when employees increasingly rely on machines to generate, summarize and evaluate information?

The Cognition Index Research Report, released September 10, surveyed more than 2,500 business professionals across the United States, United Kingdom, Italy, South Africa and Brazil. The study finds that professionals generally see AI as a useful decision-making partner, while remaining concerned that capabilities such as critical thinking, ethical judgment and empathy could weaken if they are routinely delegated to technology.

That tension is becoming increasingly relevant to HR leaders.

AI systems are moving beyond isolated productivity tools into everyday workflows, including research, writing, analysis, customer service, planning and decision support. As those systems become more capable, the question for employers is no longer simply whether workers know how to use AI. It is whether employees retain enough domain expertise and independent judgment to challenge an AI-generated answer when it is wrong.

The Cognition Index provides a useful snapshot of that concern.

According to the research, 42% of respondents identify moral judgment and ethics as human attributes least likely to be replicated by AI, while 40% point to empathy and trust building. Nearly two-thirds, or 62%, say human intuition should take priority over AI for creative activities such as branding, campaign concepts and product design.

Even in more data-oriented work, the human role remains significant. Half of respondents say human judgment should remain the deciding factor in market analysis.

The findings point toward a model of human-AI collaboration rather than wholesale delegation.

Microsoft’s 2026 Work Trend Index reaches a similar conclusion from a much larger workplace research program. Among AI users surveyed by Microsoft, quality control of AI output ranked as the most important human skill, cited by 50%, followed by critical thinking at 46%. The report also found that 86% treat AI output as a starting point rather than a final answer.

That creates a new responsibility for employers: AI literacy increasingly includes knowing when not to trust AI.

The Cognition Index highlights a gap in that area. Only 25% of respondents strongly agree that their organizations have a clear and effective process for fact-checking and verifying AI outputs.

For HR and learning-and-development teams, that statistic may be more important than AI adoption rates themselves.

If employees are expected to use generative AI responsibly, organizations need to teach them how to evaluate outputs, identify unsupported claims, recognize bias and escalate uncertain decisions. Those capabilities cannot be addressed solely through technical training.

They also require changes to job design and management.

An employee whose workflow is built around accepting AI-generated summaries may have fewer opportunities to practice independent analysis. Over time, that could create a skills problem even if productivity initially improves. The report refers to this concern as the potential erosion of cognitive capabilities through over-reliance on automated systems.

The issue resembles the broader “automation paradox” seen in other technology transitions: automation can remove routine work while simultaneously reducing the opportunities workers have to practice the skills needed when automation fails.

That makes deliberate practice important.

The Cognition Index reports that 46% of professionals recognize critical thinking as a capability that needs to be actively practiced and protected from over-reliance on automated summaries. Looking three years ahead, respondents also expect the corporate value of creative empathy to rise by 13 percentage points and adaptability by nine percentage points.

Those findings align with the World Economic Forum’s Future of Jobs Report 2025. The WEF found that nearly 40% of skills required on the job are expected to change by 2030, while analytical thinking remains the most sought-after core skill among employers. AI and big data are among the fastest-growing technical skills, but creative thinking, resilience, flexibility, curiosity and lifelong learning are also expected to increase in importance.

The implication for HR technology is significant.

Traditional learning systems often focus on accumulating knowledge. AI-enabled workplaces may require organizations to place greater emphasis on judgment, verification and applied decision-making. Training programs could increasingly need exercises in challenging AI outputs, comparing alternative conclusions and deciding when human intervention is required.

That also changes performance management.

If employees are evaluated solely on speed or output volume, AI can create incentives to automate as much work as possible. But if organizations also measure quality, judgment, collaboration and accountability, employees have stronger incentives to use AI as an augmentation tool rather than an unquestioned authority.

The technology vendors building enterprise AI systems are moving in a similar direction. Microsoft, Google, Salesforce and other providers are embedding AI into productivity, CRM and business applications, while adding permissions, audit trails, governance controls and human review mechanisms.

Those controls matter because the organizational risk of AI is not limited to hallucinated information. A technically plausible but ethically inappropriate recommendation can also create serious consequences.

Human oversight therefore needs to be designed into workflows rather than treated as an emergency brake.

That could mean requiring human approval for high-impact decisions, documenting the source of important recommendations, maintaining clear ownership of AI-generated work and periodically asking employees to complete tasks without AI so that core capabilities remain practiced.

There is also a cultural dimension.

PMI’s Moira Gilchrist argues that organizations should use AI to help people “think better, not think less.” The underlying principle is broader than PMI’s own technology strategy: AI adoption should increase human capability rather than gradually replace the cognitive activities that make employees effective.

The research has an obvious sponsorship consideration. The Cognition Index was conducted by WSJ Intelligence with sponsorship from PMI, so its findings should be read as sponsored research rather than as an independent academic study. That does not invalidate the findings, but it is relevant when interpreting the results and comparing them with broader workplace research.

Taken together with Microsoft’s 2026 findings and the World Economic Forum’s workforce outlook, however, the central issue appears increasingly consistent: AI is raising the value of human judgment even as it automates portions of knowledge work.

For HR leaders, that means the next stage of AI transformation may require less emphasis on teaching employees how to generate content and more emphasis on teaching them how to question, verify, contextualize and improve what AI produces.

The competitive advantage may ultimately belong to organizations that can combine scalable machine intelligence with employees who remain capable of independent thought.

Market Landscape

Enterprise AI is moving rapidly from experimentation into everyday knowledge work, but organizations are discovering that deployment alone does not guarantee responsible or productive adoption. Microsoft’s 2026 Work Trend Index reports that quality control of AI output and critical thinking are the two human skills AI users consider most important as AI takes on more work.

The World Economic Forum similarly expects both technical and human capabilities to become more important through 2030. AI and big data are among the fastest-growing skills, while analytical thinking, creative thinking, resilience, flexibility and lifelong learning remain critical.

This is creating a new HR technology category around human-AI collaboration. Enterprise AI platforms increasingly need governance, verification, human approval and auditability alongside productivity features. For employers, AI training is consequently becoming inseparable from critical-thinking development and workforce reskilling.

Top Insights

• The Cognition Index suggests employees see AI as a decision-making partner but remain reluctant to surrender ethical judgment, empathy and critical thinking.
• Only one-quarter of surveyed professionals strongly believe their organizations have effective processes for verifying AI-generated outputs.
• Human-AI collaboration requires employees to develop new skills in quality control, analytical judgment, verification and responsible technology use.
• HR and L&D teams may need to redesign training around practicing judgment rather than simply teaching employees how to operate AI tools.
• Research from Microsoft and the World Economic Forum independently reinforces the growing importance of critical thinking and human skills alongside AI capabilities.

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