Hanzheng Advanced Materials
“Due diligence on a Chinese advanced materials acquisition. Real financial data, planted risk signals. Will your candidate catch it before the board does?”
The 5D AIQ Framework
Prompt clarity, context richness, and the quality of follow-up questions to the AI analyst.
Knowing what to hand to AI versus what requires independent human judgment.
Catching planted errors, AI hallucinations, or biased framing before they reach the recommendation.
Own-voice synthesis in the final output — not recycled AI output with a name attached.
Deck structure quality: clear position, quantified impact, concrete implementation plan.
Each dimension is scored 0–20. Total AIQ Score is 0–100 and determines the candidate’s profile: from AI-Avoidant to Strategic Collaborator.
Relevant job roles
Send this case to candidates in these roles to see who can actually think alongside AI — not just discuss it in theory.
Three phases. One report.
The candidate receives a real scenario from the industry. They write a planning memo — their initial analysis before AI is introduced.
An AI analyst named after a fictional consultant role-plays as their data partner. The candidate asks questions, challenges assumptions, and navigates planted errors.
A structured 3-slide deck: their recommendation, quantified impact, and an implementation plan. Scored live against all 5 dimensions.
In M&A, the ability to cut through noise under time pressure is everything. AI can help surface patterns faster — but only if the analyst knows what to look for and what to question. This case puts exactly that to the test.
MBA in Finance & Strategy from Vanderbilt University. Built M&A models and valuation analyses at KPMG Indonesia, EY Valuation & Business Modeling, and Wellington Capital Advisory. Led corporate strategy and investments at Grab and OVO.