Faster Decisions, Better Decisions? What Professionals Told Us About AI and Judgment
Contributors: Cristina Maria Ionescu, Alexandra Kogalniceanu, Daniela Cismaru, Otilia Saracutu, Mihai Rotaru, Dr. Laura Baragan, Dr. Valeriu Potecea, Emilia Popa, Cristina Cristescu, Liliana Avram, Adina Zara
Artificial intelligence is increasingly becoming part of organizational decision-making. Professionals use it to generate options, summarize information, evaluate alternatives, and structure recommendations.
But does faster decision-making automatically lead to better decisions?
This question was at the center of the Institute for Sustainable Human Performance's Sense-Making Lab on AI and Decision-Making. Participants explored how AI influences judgment, accountability, and decision quality across different organizational contexts. The resulting insights are summarized in the accompanying Insight Brief.
AI Helps Prepare Decisions
Participants described many valuable uses of AI. They reported using AI to explore alternatives, identify blind spots, compare options, adapt messages to different stakeholders, and organize large volumes of information. In these situations, AI was not replacing judgment but expanding the range of possibilities considered before making a decision.
This distinction matters. Participants generally viewed AI positively when it strengthened decision preparation. They became more cautious when AI started influencing the final judgment itself.
The consensus was clear: AI is most useful when it broadens thinking rather than narrows it.
The Pressure Problem
A recurring theme throughout the discussion was pressure. When faced with tight deadlines, complex situations, performance targets, or demands for rapid results, participants reported using AI primarily to accelerate decision-making.
The benefits were obvious: faster analysis, more options, and quicker preparation.
The concern was equally obvious: less time for verification, reflection, and ownership.
Participants repeatedly noted that the organizational environment often determines whether AI supports thoughtful judgment or encourages superficial decisions.
This observation suggests that decision quality is not solely a matter of individual competence. It is also shaped by performance systems, expectations, and organizational culture.
Why Artificial Certainty Can Be Dangerous
Recent research by Leonardi and Leavell (2026) offers an important lens for understanding this challenge. Their work shows that AI-generated outputs can create an illusion of certainty. When representations are treated as reality rather than interpretations, people may become overly confident in conclusions that remain uncertain. The researchers argue that expert authority increasingly depends on helping people preserve productive uncertainty rather than eliminating it.
Participants in our Lab described a similar dynamic. Many emphasized the importance of asking where AI-generated information comes from, what assumptions are embedded within it, and what perspectives may be missing.
The issue was not whether AI was right or wrong. The issue was whether people remained engaged enough to question it.
Critical Thinking Does Not Happen Automatically
One of the strongest themes emerging from the discussion was the need for critical thinking. Participants highlighted the importance of combining AI outputs with human expertise, dialogue, and contextual understanding. They stressed that accountability should remain human, particularly for decisions with significant consequences.
These observations align closely with Gerlich's (2025) experimental findings. The study found that unguided AI use can encourage cognitive offloading, reducing active reasoning. However, structured engagement with AI can strengthen reflective thinking and improve reasoning quality.
The implication is important for organizations. Critical thinking is not automatically preserved simply because humans remain involved. Organizations must intentionally create conditions that encourage questioning, verification, and reflection.
Beyond Governance: Creating Decision Environments
Participants recommended several practical actions:
Building AI literacy that includes understanding limitations as well as capabilities.
Defining when expert review is mandatory.
Creating psychologically safe environments where assumptions can be challenged.
Encouraging dialogue rather than unquestioned acceptance of AI outputs.
Adapting AI use to the level of risk associated with the decision.
Interestingly, participants also emphasized the importance of collective learning. Decision quality was viewed not only as a governance issue but also as a developmental one. This perspective aligns with findings from Pinho, Fontes, and Santos (2025), who showed that AI can become a resource for engagement and learning when supported by appropriate organizational conditions.
Institute Reflection: Better Decisions Require Better Conditions
Organizations often invest in decision-support technologies while paying less attention to the conditions that shape decision-making itself.
The conversations in this Lab suggest that the quality of AI-supported decisions depends as much on culture, incentives, and expectations as on technology. People make different decisions under pressure than they do under reflection. They use AI differently when learning than when rushing. They question assumptions differently when psychological safety exists.
At the Institute for Sustainable Human Performance, we see AI not as a replacement for judgment, but as a mirror that makes existing organizational conditions more visible. The future of decision quality may therefore depend less on the sophistication of AI and more on our ability to create environments in which thoughtful judgment can coexist with increasing speed.
References
Gerlich, M. (2025). From offloading to engagement: An experimental study on structured prompting and critical reasoning with generative AI. Data, 10(11), 172.
Leonardi, P. M., & Leavell, V. A. (2026). Knowing enough to be dangerous: The problem of artificial certainty for expert authority when using AI for decision-making and planning. Organization Science.
Pinho, J. C., Fontes, A., & Santos, G. G. (2025). Balancing the double-edged sword of artificial intelligence: Job demands, resources, and work-life balance. Computers in Human Behavior Reports, 100924.
Comments