AI Enablement Lead (OKC) Non-Safety Sensitive

Mathis Home•Oklahoma City, OK

1d•Onsite

About The Position

The AI Enablement Lead will help departments across the company use AI safely and productively. This role involves finding valuable AI use cases, teaching employees to use approved AI tools, creating reusable patterns and workflows, and measuring adoption and value. The lead will partner with various departments like Engineering, IT Operations, Human Resources, and Risk to ensure AI use aligns with company policies and security standards. They will also manage the AI Enablement Specialist and support the AI service-desk implementation.

Requirements

5-10 years of experience in training, enablement, business analysis, process improvement, or a technology-facing role.
Demonstrated experience delivering training and building documentation for non-technical audiences.
Hands-on experience with generative AI tools and prompt design, with the judgment to recognize where AI is and is not appropriate.
Experience measuring adoption and reporting business value to leadership.
Working knowledge of data-privacy, information-security, and acceptable-use considerations for AI in a business setting.
Experience partnering with technical teams to move proven ideas into supported solutions.
Strong communication skills, both written and verbal.
Ability to work independently and as part of a team.
Ability to repetitively use arms, hands and fingers.
Ability to communicate effectively with team members.
Positive attitude when working with internal and external customers.
Knowledge of employment and safety procedures.

Nice To Haves

Degree in Business, Information Systems, Communications, Education, or related field preferred.
Prior experience supervising, coaching, or leading staff preferred.

Responsibilities

Help departments across the company use AI safely and productively.
Find valuable AI use cases within business departments and qualify each one against a named owner and a measurable outcome.
Teach employees to use approved AI tools through training sessions, office hours, and hands-on support.
Create approved patterns, reusable prompts, and repeatable workflows that employees can apply to daily work, and document good practices.
Measure adoption and value, and report monthly on active use, repeatable workflows, cost, measured value, and promoted enterprise solutions.
Hand proven ideas to engineering when they need a durable company solution.
Help employees move from experimentation to reliable daily use, and track recurring needs that indicate a broader company requirement.
Support execution of the Merchandising AI Roadmap, beginning with Inventory agents, partnering with the merchandising business owner and the Director of Engineering & AI on baseline, data readiness, pilot milestones, human-approval controls, adoption, and measured business result, and report biweekly.
Ensure human-approval and risk controls are defined and observed for every AI workflow placed in front of employees.
Lead the AI Enablement Specialist, including hands-on employee support, training and office hours, documentation, and tracking of recurring needs.
Partner with IT Operations on AI and automation in the support model, including approved answers drawn from company documentation, guided password, access, software, printer, and device troubleshooting, approved self-service workflows, and ticket creation, summarization, categorization, prioritization, and routing.
Support the AI service-desk implementation sequence through baseline and knowledge preparation, a pilot with people in the loop, expansion and stabilization, and the ninety-day proof period, improving the knowledge base, workflows, and AI responses as new issues appear.
Maintain the catalog of approved AI tools and use cases, including intake, evaluation, and a documented approval path for new requests.
Partner with Human Resources, Risk, and IT Operations to keep AI use aligned with company policy, data-privacy requirements, and information-security standards, and refresh that guidance as tools change.
Track AI tool licensing, consumption, and cost by department, and report cost against measured value.
Build a role-based enablement curriculum, including onboarding content for new employees and refresher training as tools and approved patterns change.
Establish a feedback loop that captures failures, unsafe or inaccurate outputs, and near misses, and route those findings to engineering and policy owners for correction.
Enforce all company policies and procedures and perform disciplinary actions when necessary.
Ensure the safety and productivity of employees.
Perform any other duties as directed by management.