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A Bohmian Framework for Quantum Potentials in AI Governance: Mills-Validated Empirics for Value Measurement

A Bohmian Framework for Quantum Potentials in AI Governance: Mills-Validated Empirics for Value Measurement
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Author(s): Milan B. Vemić (Faculty of Business Studies and Law, University Union - Nikola Tesla, Belgrade, Serbia)
Copyright: 2026
Volume: 5
Issue: 1
Pages: 32
Source title: International Journal of Business Strategy and Automation (IJBSA)
Editor(s)-in-Chief: Muhammad Abu Naser (London Metropolitan University, United Kingdom)
DOI: 10.4018/IJBSA.404750

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Abstract

Quantum-substantiated AI provider value measurement model grounded in regulatory uncertainty and Bohmian mechanics institutes AI Growth-Stability Evolution Equation, ΔG⋅ΔS≥k*(1+β*IF), quantifies innovation potential and regulatory compliance trade-offs through quantum potential Q(r,t), classical regulatory forces V(r,t), and internal governance U(x). While not regulatorily tested, Mills' four inductive methods validated Lennard-Jones-Sheldrake-Aharonov-Bohm findings, correlating with Hierarchical Reasoning Model (HRM), proving nonlocal influence as a universal organizing principle across interdisciplinary potentials. Correspondence and complementarity methods: (1) mathematically enact time-dependent AI regulatory Hamiltonian Ĥ=[-(ħ2/2m)∇2+V(r,t)+Q(r,t)+U(x)]ψ(r,t); (2) capture quantum-to-classical shifts in Boolean algebra (a∧b∧c)∨(a∧b∧c′)∨(a∧b′∧c)∨(a′∧b∧c); (3) enable proof with AI solenoids proving field-free regulatory interference. Quantized harmonic oscillator models, spectral coherence (E=hv), capture invisible value indicators of “AI curvature”, enable nuanced evaluation.

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