Artificial intelligence is transforming how organizations manage customer relationships. From chatbots and predictive analytics to sentiment analysis and automation, AI-enabled Customer Relationship Management (CRM) systems promise personalized engagement, streamlined workflows and stronger decision-making.
Yet despite heavy investment, many companies struggle to translate these tools into measurable business gains. In his doctoral dissertation, Praveen Manimangalam, a student in FIU Business’s Doctorate in Business Administration (DBA) program, examines why.
Using data from 300 organizations across technology, finance, retail, healthcare and manufacturing sectors, the study analyzes how AI-CRM capabilities, strategic AI investments and organizational strengths influence operational efficiency, customer satisfaction and revenue growth.
Using advanced statistical analysis, the model explains approximately 74 percent of the variance in business performance across industries.
The findings challenge a common assumption.
“I initially expected AI integration to have a significant direct impact on business performance,” Manimangalam said. “But the data showed that AI technology alone does not produce measurable gains.”
While tools such as chatbots, predictive analytics and automation are widely adopted, their direct impact proved weak. Instead, the strongest drivers were organizational capabilities — particularly innovation capacity, employee expertise and a customer-centric business model.
“AI tools can generate insights, but without strong organizational capabilities, those insights never translate into improved outcomes,” he explained.
Innovation capability emerged as the most powerful predictor, highlighting the importance of experimentation and a culture that supports scaling new ideas. A clearly embedded customer-focused strategy significantly enhanced results, and employee expertise — including AI literacy and technical skill development — played a critical role.
In this framework, AI functions as a performance amplifier rather than a performance engine.
“Too many companies view AI as a silver bullet,” Manimangalam said. “Technology doesn’t replace strategy — it enhances it.”
The study also explains why outcomes vary widely. High implementation costs, poor data quality, infrastructure limitations, and employee resistance frequently undermine AI initiatives. Firms that prioritize software purchases but neglect workforce development and process redesign often struggle to justify their investments.
Manimangalam emphasizes that strategic AI investment still matters — but as an enabler. “Spending on AI absolutely matters. But long-term budgets and executive sponsorship strengthen internal capabilities — and that’s what ultimately drives performance.”
Industry context further shapes results. Service-oriented sectors with high customer interaction and data intensity benefit more directly from AI-CRM adoption than product-oriented industries facing structural or regulatory constraints. The study also controls for company size to ensure findings are not simply driven by resource differences.
“You can’t apply a one-size-fits-all AI strategy,” he added. “Effectiveness depends on the environment the organization operates in and how prepared it is internally.”
By integrating the Resource-Based View, Dynamic Capabilities Theory and the Technology-Organization-Environment framework, the research moves beyond technology-centric explanations.
“We tend to treat technology, strategy and environment as separate conversations,” Manimangalam said. “Performance improves when those elements are aligned.”
The study also addresses a gap in prior research.
“Much of the literature looks at individual AI tools in isolation,” he noted. “There hasn’t been enough cross-industry, data-driven evidence showing how technology, organizational readiness and context work together.”
Together, the findings shift the leadership focus — not how much to spend on AI, but whether organizations are prepared to use it effectively.
The research was recently presented at the American Chapter of The Academy of Sustainable Finance, Accounting, Accountability & Governance 2026 Conference and will be published in conference proceedings associated with venues including the Association for the Advancement of Artificial Intelligence, Cognitive Innovation Conference and CERALE (Centre d'Etudes et de Recherche Amérique latine Europe) 2026. Manimangalam is currently developing a prototype system based on the research and preparing to file a patent related to the architecture.