I’m launching StudentRisk AI, an AI-powered Early Warning System designed to help schools and universities identify at-risk students before disengagement or dropout occurs. This is one of three major AI platforms I am developing as part of a new, long-term innovation roadmap as I begin my second innings in my career — with a clear focus on applying AI to real-world, high-impact problems. Built for the Salesforce Agentforce + Tableau Hackathon, StudentRisk AI combines: • Machine-learning models to predict student risk • Tableau Next for real-time, explainable analytics • Salesforce Agentforce to turn insights into automated interventions The platform is designed to be global, scalable, and transparent, so institutions in any country can adapt it to their education systems.

“Feedback, ideas, and collaboration are welcome.”

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Live demo: https://lnkd.in/gJruweeQ

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ALSO Try out the StudentRisk AI live demo: studentrisk.admnwizard.com https://studentrisk.admnwizard.com Ask real-world questions about student risk, performance, and well-being — powered by AI + Tableau analytics. StudentRisk AI – 36 Smart Chatbot Questions

A. Overall Risk Intelligence Who are the top 10 students at highest risk right now? How many students are in the Critical risk category? Show me the distribution of students by risk category. Which school has the highest average risk score? Which city has the most high-risk students? Which grade is the most vulnerable? What is the overall average risk score? Which students have risk scores above 80? Which students have improved their risk score recently? Who should be prioritized for intervention this week?

B. Student-Specific Insights What is the current risk score for student 105? Why is student 105 categorized as Critical? Which factors contribute most to student 101’s risk? Is student 104 safe academically? Compare the risk of student 102 and 103. Has student 110 improved or worsened? Which student has the highest wellbeing risk? Which student has the worst academic risk? Which student is most likely to drop out? Who has high attendance but still poor academic performance?

C. Academic & Attendance Analysis Which students are struggling academically despite good attendance? Which students have declining exam trends? Who has the lowest exam scores? Which students have frequent absences? Which students show learning difficulty patterns? Who is suffering from exam shock? Which students are academically stable?

D. Wellbeing & Socioeconomic Risk Which students are showing burnout risk? Who has high stress and multiple counseling visits? Which students are affected by financial hardship? Who is suffering from the digital divide?