AI Program Manager

Insperity•Houston, TX

2d•Hybrid

About The Position

This position is responsible for driving Insperity’s AI capabilities by providing enterprise leadership, expertise, and delivery support for high-impact AI solutions to employees, divisions, and clients. The role serves as the connective tissue between AI Strategy, ITS, and business partners—translating priority outcomes into an executable AI portfolio across the build, buy, and blend spectrum and ensuring the support mechanisms (governance, enablement, measurement, and adoption) are in place to drive quality and sustained impact. Depending on evolving enterprise needs, this role may (1) support our proprietary Insperity AI Platform and agent ecosystem, (2) enable function-specific tools and capabilities within divisions (including evaluation, selection, training, and deployment of licensed/point AI tools), and/or (3) help leverage AI embedded in existing SaaS platforms. The AI Program Manager partners closely with division stakeholders, ITS, Enterprise Analytics, Product Management, Legal, InfoSec, and external technology vendors to deliver integrated AI capabilities that improve productivity, efficiency, quality, user experience, and business value.

Requirements

Bachelor’s Degree or higher in business, information systems, computer science, analytics, engineering, or related field is required.
Three to five years of experience in program or project management, product operations, business analysis, or technology delivery roles is required.
Demonstrated experience managing cross-functional programs with clear business outcomes and measurable success criteria.
Strong understanding of business workflows and how to translate work into opportunities for automation, augmentation, and improved decision-making through AI and analytics.
Working knowledge of AI concepts, tools, and lifecycle considerations, including generative AI, agentic workflows, evaluation approaches, and the operational realities of deploying AI in production.
Proficiency in project management methodologies and tools (e.g., Smartsheet, Jira, Monday).
Excellent communication, collaboration, and problem-solving skills, with the ability to translate technical concepts for business audiences and business needs for technical audiences.
Ability to think strategically and creatively and adapt to changing needs and priorities.
Strong networking and relationship-building skills, particularly across Sales, Marketing, Technology, and external vendor partners.
Detail oriented, organized, and able to handle a multi-task environment with skill and accuracy.
Working knowledge of agile, iterative development practices for AI applications and software programs.

Nice To Haves

Experience working in a complex, cross-functional environment (business, technology, risk/compliance) and facilitating stakeholder alignment across multiple teams is preferred.
Experience with AI and analytics initiatives—including generative AI and agentic workflows, AI embedded in SaaS platforms, and/or enterprise enablement of licensed AI tools—is preferred.
Familiarity with enterprise platforms and collaboration tools where AI is increasingly embedded (e.g., CRM, service platforms, HRIS, content/knowledge systems, and Microsoft 365) and the implications for integration, user experience, and adoption.
Familiarity with AI governance frameworks and responsible AI principles, including data privacy, security controls, evaluation and monitoring expectations, and appropriate use guidance.
Experience supporting vendor evaluation, contracting, and ongoing management for technology platforms is preferred.
Comfort working in a high-visibility role partnering with senior leaders across multiple functions and translating between business outcomes and technical execution.

Responsibilities

Drives AI program execution for an assigned business domain or enterprise priority area, translating business outcomes into scoped programs that span the build, buy, and blend spectrum and align with the enterprise AI portfolio managed by the AI Strategy team.
Designs and runs the intake, evaluation, and prioritization process for AI opportunities surfaced by business partners, applying structured frameworks and ensuring opportunities map to measurable outcomes, risk posture, and readiness.
Facilitates use case discovery and definition (workflow mapping, user research, requirements, and success metrics), partnering with SMEs to translate frontline needs into clear program deliverables and reusable patterns.
Depending on the initiative, may be responsible for end-to-end delivery coordination across design, technical development, testing, rollout, and optimization—ensuring appropriate artifacts, decisions, and stage gates are in place for reliable production deployment.
Partners with ITS, Enterprise Analytics, platform owners, and Product Management to deliver integrated AI solutions, including proprietary AI applications and agents, AI embedded in SaaS platforms, and licensed/point AI tools deployed within functions.
Champions agile, iterative delivery practices for AI programs, establishing an operating cadence with stakeholders and providing consistent reporting against roadmap commitments, dependencies, and risks.
Leads or supports vendor and tool evaluation (requirements, due diligence, pilots, and selection) and works with Procurement, Legal, InfoSec, and IT to ensure contracts, controls, and support models are appropriate for the intended use.
Partners with Legal, InfoSec, IT, and AI governance bodies to ensure AI initiatives meet organizational policies, ethical guidelines, and regulatory requirements, and that appropriate controls and documentation exist for auditability and trust.
Maintains program documentation, including roadmaps, status updates, risk/issue logs, decision records, release plans, and adoption plans—ensuring transparency for business partners and AI Strategy leadership.
Leads change management, communication, and training efforts for users adopting AI capabilities, building AI literacy, establishing feedback loops, and supporting the broader culture of responsible AI adoption.
Supports the health of the agent ecosystem and user experience by partnering on standards for agent behavior, guardrails, evaluation approaches, versioning/release practices, and consistent interaction patterns across channels and platforms.
Tracks program performance against agreed metrics (adoption, time saved, quality/error reduction, cycle-time improvements, customer experience, risk reduction, and financial impact as applicable) and partners with Enterprise Analytics to mature measurement and value realization over time.