IEEE SoutheastCon · Xplore
Investigating how organizations convert artificial intelligence investment into measurable business performance — across agentic systems, enterprise CRM, and autonomous logistics.
Dr. Praveen Manimangalam studies how organizations transform investments in artificial intelligence into measurable business outcomes. His interdisciplinary work spans agentic AI, enterprise systems, autonomous technologies, innovation governance, and organizational capabilities.
Drawing on nearly two decades of combined academic and industry experience, he pairs rigorous empirical methods with practical insight to advance responsible AI adoption and enterprise transformation. His work appears through venues including IEEE, AAAI, INFORMS, and AIPLA, and he contributes to the scholarly community through peer review, mentoring, judging, and conference leadership.
Peer-reviewed proceedings, professional publications, and forthcoming work in agentic enterprise systems and autonomous logistics.
Investigating the Determinants of Business Performance: The Interplay of AI-Integrated CRM, Strategic AI Investments, and Organizational Capabilities
Drawing on survey data from 307 organizations across the technology, finance, retail, healthcare, and manufacturing sectors, this dissertation examines why heavy investment in AI-enabled customer relationship management so often fails to translate into measurable business gains. Using structural equation modeling, the study tests how AI-CRM capabilities, strategic AI investment, and organizational strengths jointly shape operational efficiency, customer satisfaction, and revenue growth — a model that explains roughly 74% of the variance in business performance across industries.
The central finding challenges a common assumption: AI technology alone does not drive performance. The strongest predictors are organizational capabilities — innovation capacity, employee expertise, and a customer-centric operating model — with AI functioning as an amplifier of those capabilities rather than an engine in its own right. Industry context further moderates the effect, with service-oriented, data-intensive sectors benefiting more directly than product-oriented ones. The work integrates the Resource-Based View, Dynamic Capabilities Theory, and the Technology–Organization–Environment framework to move beyond technology-centric explanations of AI value creation.
Committee Chair: Dr. Hemang Subramanian · Florida International University
Full text and slides will be available after the defense on June 29, 2026 — the dissertation will link to the official FIU Digital Commons record.
Three patent-pending platforms and active research builds in agentic enterprise systems and autonomous logistics.
A self-configuring CRM that removes the configuration bottleneck — describe your business in plain language, and the system builds itself.
Traditional CRM demands an IT team, a six-figure budget, and months of setup before it does anything useful. ASICRM-Pro removes that configuration debt entirely: from a plain-language description of the business, an agentic pipeline generates the full data schema, instantiates context-inferred automation workflows, deploys coordinating Sales, Service, Marketing, and Finance agents, and then self-optimizes through a reinforcement-learning loop — natively coupling CRM with procurement along the way.
A high-assurance, distributed framework for BVLOS-compliant autonomous UAV logistics — engineered for FAA Part 108 readiness and 100% command integrity under adversarial conditions.
An autonomous, high-assurance UAV system for fire response and critical emergency missions — a Drone Tree Network module presented at the IAFC Technology Summit International.
Eighteen-plus years spanning U.S. enterprise product leadership in healthcare and SaaS, and earlier IT leadership and consulting across Asia and Africa — alongside scholarly service and professional recognition.
76 reviews · 18 scholarly venues
Spanning international business, information systems, human–computer interaction, management, and engineering.
Scope, build, and ship AI and agentic products — from problem framing and roadmapping to cross-functional delivery and measuring real outcomes. Taught through the actual decisions, trade-offs, and lessons behind a live agentic-CRM build, not generic theory.
Enrolling soonAgile and SAFe delivery for software and AI initiatives — planning, execution, and stakeholder alignment, grounded in PMP and SAFe practice.
Protecting AI innovation in practice — patents, trade secrets, and disclosure strategy for engineers and product leaders building in the age of AI.
Lessons from building secure UAV logistics systems — autonomy, safety, and the FAA Part 107/108 regulatory landscape for AI-driven drones.
I share recorded talks, course previews, and build-in-public notes from developing agentic-AI products. The channel is new — videos rolling out soon.
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I'm open to co-authoring, research projects, panels, advisory work, and AI & innovation initiatives. If something here resonates, tell me a little about yourself and I'll be in touch.
Open to faculty positions, product and project leadership roles, research collaboration, advisory work, and speaking on agentic AI and autonomous systems.