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AI Enablement & Adoption Specialist

Job in Addison, Dallas County, Texas, 75001, USA
Listing for: MPOWERHealth
Full Time position
Listed on 2026-09-05
Job specializations:
  • IT/Tech
    AI Business & Operations, AI Engineer (Applied/Software), AI Evaluation
Job Description & How to Apply Below

The AI Enablement and Adoption Specialist will lead the practical adoption of enterprise generative AI capabilities, with a focus on leveraging enterprise market-leading AI platforms across business and technology teams. This role will partner with department leaders and subject-matter experts to understand business processes, identify appropriate AI use cases, and develop secure, repeatable AI-assisted workflows. The specialist will help users apply AI effectively through prompt development, platform capabilities and skills, training, human-in-the-loop controls, and responsible-use guidance, particularly when working with confidential information and protected health information (PII & HIPAA).

ROLE AND RESPONSIBILITIES

  • Serve as the organization’s primary expert on enterprise market-leading and approved generative AI tools, including their capabilities, limitations, and appropriate uses.
  • Partner with department leaders, designated AI champions, and subject-matter experts to understand workflows, identify opportunities, and prioritize AI use cases based on value, feasibility, risk, and data sensitivity.
  • Translate business and technology needs into practical AI-assisted solutions without acting as the functional subject-matter expert or final decision-maker.
  • Design, test, document, and maintain reusable prompts, platform capabilities and skills, instructions, templates, and AI-enabled workflows tailored to departmental needs.
  • Help teams organize source documents, examples, instructions, and contextual information to improve the accuracy, consistency, and usefulness of AI-generated outputs.
  • Recommend the appropriate use of chat, platform capabilities and skills, AI enabled coding, document analysis, APIs, connectors, MCP tools, and other approved capabilities.
  • Define input requirements, expected outputs, validation criteria, human-in-the-loop checkpoints, approval requirements, and escalation procedures for AI-assisted workflows.
  • Work with department subject-matter experts to evaluate outputs for accuracy, completeness, consistency, and business usability.
  • Assist technology and data teams with AI-enabled activities such as SQL development, data integration, schema analysis, Power BI, Excel, Power Apps, analytics, code review, testing, technical documentation, and syntheticdata creation.
  • Assist knowledge workers and business teams with summarizing emails, meetings, and documents; drafting communications; organizing tasks; preparing for meetings; analyzing information; and creating presentations and business narratives and increasing overall efficiencies.
  • Support document-intelligence use cases, including extracting structured information, comparing documents, summarizing content, and enabling approved natural-language access to sensitive documents.
  • Partner with Finance, Accounting, Revenue Cycle, Clinical, and other business teams to develop controlled AI assisted workflows, while ensuring qualified departmental experts retain responsibility for validation and final decisions.

    Develop and deliver role-based training, demonstrations, job aids, and hands-on coaching to help users apply AI effectively and responsibly in their daily work.
  • Explain generative AI risks and limitations, including hallucinations, incomplete or outdated information, inconsistent outputs, data exposure, and over reliance on AI-generated recommendations.
  • Partner with Security, Privacy, Compliance, Legal, Data, and Technology teams to ensure AI solutions comply with HIPAA, PHI and PII requirements, organizational policies, security controls, and contractual obligations.
  • Help maintain guidance identifying approved, restricted, and prohibited AI tools, features, data types, integrations, and use cases.
  • Monitor adoption, user feedback, productivity gains, output quality, risk indicators, and business value, and recommend improvements to workflows, training, governance, and technology configurations.
  • Developing quantitative metrics to ensure desired outcomes are met such as accuracy, efficiency, productivity, and other expected success criteria.
  • Maintain awareness of changes to enterprise, market-leading AI platforms and contribute to the…
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