A view of Executive Assessment from the field – Professional judgment with AI-supported augmentation
Why it matters
AI has the power to enhance assessment...
“AI transforms idea development and research design by providing valuable insights and optimising methodologies.”1
though it comes with meaningful risks.
“AI use also comes with potential risks such as over-reliance on these systems, which may result in impaired critical thinking and altered memory retention.”2
As Psychology practitioners, we have an important role to play in how this pans out.
“Psychology is at the forefront of one of the most consequential technological shifts in human history—not reacting to it but shaping it. That is precisely where we belong.”3
What it can look like in Executive Assessment
01
Pre‑Interview
General phases pre-AI
•Pre-call with the hiring team: Ask semi-structured questions and take notes.
•Review materials (e.g. JD, resume, psychometric results) to spot trends and develop hypotheses
With responsible AI + humans
•Trained AI tools to support company, role, and psychometric research, interpretation, and preparation.
•Trained AI as thought partner: Support hypothesis formation and insights
•AI organize materials for the interview and debrief.
02
Interview
General phases pre-AI
•Ask semi-structured questions and take good notes.
With responsible AI + humans
•Real-time transcription: May consider use of AI transcription capability or recording.
03
Synthesis post‑interview
General phases pre-AI
•Review interview notes with psychometrics and context docs
•Highlight sections and comments in interview notes
•Synthesize into themes and develop conceptualization, while also documenting evidence
With responsible AI + humans
•Trained AI tools to make use of highly contextualized trends (e.g. by function and level). Leverage AI to make use of contextual detail from existing company data (public data, shared material, synthesized stakeholder notes) to help inform conclusions.
•Trained AI as thought partner: Iteratively conceptualize key themes, draw insights, surface evidence, challenge assumptions, and ensure breadth of coverage of relevant questions.
04
Report outcomes
General phases pre-AI
•Begin with a blank template for narrative report
•Leverage boilerplate language from deterministic psychometric reports to draft narrative report
•Assemble notes for debrief meeting
•Prepare for feedback and development coaching by re-reading interview notes; highlight critical points for ease in conversation flow
With responsible AI + humans
•Trained AI tools to aid in early report draft preparation and recommendations. Preserve linkage to source data (psychometrics, interview notes, etc.). Enable AI to evidence this. Consider AI-suggested copy-editing recommendations with human review and confirmation.
•Trained AI as thought partner: Consider use of AI-supported coaching tools for feedback prep.
Practical recommendations for practitioners in Executive Assessment
Own your work
•Intentionalize your workflow. Create consistency mechanisms, with space for adjustment, to ensure process integrity.
•Know yourself. Where do you excel? Where do you struggle? What are your vulnerabilities? When do these appear?
•Challenge yourself to learn new ways to achieve outcomes by learning new skills.
Avoid cognitive decline
•Iterate, iterate, iterate. Then iterate.
•Capture insights in a style that works for you.
•Avoid the “easy button”: be scrutinizing, challenging, and surface counterfactuals. Stay curious.
•Make good use of conceptual frameworks to ground ideation.
Stay continuous improvement-minded
•Monitor outcomes, continuously improve.
•Scan for new opportunities and take action on identified areas for improvements. Be challenging and creative (notice repetition, listen to stakeholders, lean into empathy).
•Be on the lookout for opportunities to improve highly contextualized AI support tools.
Stay ethical
•Ensure rigid guardrails. Preserve confidentiality, ensure source connectivity, minimize unnecessary personal data exposure.
Where may we go from here?
Elevate individual insight to the enterprise level.
Work in close partnership with companies to understand pain points and where insight from assessment may add practical value.
Continue to strengthen security and confidentiality protocols.
1: Khalifa, M., & Albadawy, M. (2024). Using artificial intelligence in academic writing and research: An essential productivity tool. Computer Methods and Programs in Biomedicine Update, 5, 100145. https://doi.org/10.1016/j.cmpbup.2024.100145
2: Bai, L., Liu, X., & Su, J. (2023). ChatGPT: The cognitive effects on learning and memory. Brain-X, 1, e30. https://doi.org/10.1002/brx2.30
3: Evans, A. C., Jr. (2026, July 1). Psychology's moment in the AI revolution: APA's new Center for Behavioral Science and AI brings psychological expertise to technology. Monitor on Psychology, 57(5), 10.
