The integration of artificial intelligence (AI) into psychological assessment is transforming clinical practice, offering scalable solutions that complement traditional methods. This presentation introduces the Measure for Artificial Intelligence-based Psychopathology Assessment (MAPA), a platform of digital assessment tools designed to analyze natural language with high contextual accuracy. MAPA operates through a mobile interface accessible on standard smartphones and is structured around a semi-structured interview format, where patient speech is recorded, transcribed, and analyzed by transformer-based language models (TLMs). The system then generates structured clinical reports mapping disorder-specific symptomatology to support clinicians. MAPA represents a growing suite of tools, of which two modules are currently available: MAPA-OCD, developed for obsessive-compulsive disorder, and MAPA-ANX, developed for pathological anxiety. Tool development followed a multidisciplinary process, combining AI engineering expertise with clinical specialization in psychopathology to ensure both technological robustness and clinical validity. Validation was performed with two clinical cohorts: 30 adults diagnosed with OCD for MAPA-OCD, and 38 adults with anxiety disorders for MAPA-ANX. Participants provided extended speech samples, and AI-generated reports were benchmarked against traditional clinician-administered assessments. Results demonstrated strong stability across repeated analyses, high agreement with clinician ratings, and compelling evidence of external validity, supporting the reliability of MAPA in detecting disorder-specific symptoms. Three major contributions emerge: first, evidence that TLMs can accurately parse complex clinical narratives across distinct psychopathologies; second, demonstration of the feasibility of remote digital screening via accessible mobile technology; and third, the potential to enhance clinical efficiency by providing clinicians with structured, AI-supported reports. Together, MAPA-OCD and MAPA-ANX illustrate the promise of MAPA as an innovative framework for integrating AI into clinical practice. Future directions include refining algorithms for cultural and linguistic variability, expanding validation with diverse populations, and exploring adaptive, real-time feedback during assessments.