Director, Enterprise AI Automation & Transformation

Wetherill Associates Inc•Miramar, FL

5d•Onsite

About The Position

WAI is creating a new enterprise AI capability focused on practical business impact, aiming to improve workflows, reduce manual effort, increase speed and quality, support better decisions, and help teams use AI-enabled tools responsibly. The Director, Enterprise AI Automation & Transformation will be the business-facing leader responsible for building this capability from the ground up. This role leads the business side of a business-led, IT-governed operating model, shaping how WAI identifies, prioritizes, launches, governs, adopts, and measures AI-enabled use cases across business functions. The goal is to move WAI from AI interest to AI operating discipline by building a repeatable model for finding opportunities, designing solutions, partnering with IT, enabling business teams, and proving value through productivity, quality, speed, service, cost avoidance, and employee or customer experience improvements. This is a hands-on enterprise transformation role focused on turning AI, automation, workflow redesign, and operating discipline into measurable business outcomes.

Requirements

Operate in ambiguity, build from zero-to-one, and create measurable enterprise impact.
Experience in business transformation, process improvement, operations, automation, product management, consulting, enterprise technology-enabled change, or a related field.
Track record of turning complex or ambiguous business problems into practical roadmaps, workflows, pilots, requirements, adoption plans, and measurable outcomes.
Comfortable working with senior business stakeholders, department leaders, managers, technical teams, vendors, and front-line users.
Executive presence, strong facilitation skills, clear communication, and the ability to build trust across functions.
Working fluency with AI and automation concepts such as AI agents, workflow orchestration, knowledge retrieval, prompting, human-in-the-loop design, testing, monitoring, adoption, and governance.
Ability to partner with technical teams on data access, security, architecture, integrations, production release, and support models without needing to own day-to-day technical infrastructure yourself.
Strong judgment about where automation creates value, where human review must remain in place, and how to balance speed, business value, risk, controls, and long-term scalability.
Energized by building standards while the capability is still evolving.

Nice To Haves

Experience with enterprise systems such as ERP, CRM, customer service platforms, collaboration tools, knowledge repositories, reporting tools, workflow systems, or related platforms.
Experience with tools or platforms such as Microsoft Copilot, Power Platform, Power Automate, Azure AI, Enterprise LLM tools, RAG frameworks, workflow tools, or similar technologies.
Experience building or scaling a new capability, automation program, transformation office, AI governance forum, digital initiative, enterprise productivity program, or center of excellence.
Certifications or formal training in project management, Lean / Six Sigma, product management, business process management, data analytics, AI, automation tools, or change management.

Responsibilities

Lead WAI's enterprise AI program, including use-case intake, prioritization, roadmap development, governance routines, adoption planning, and ROI tracking.
Partner with leaders and process owners across functions such as Finance, Customer Service, Supply Chain, Sales Support, Operations, HR, Product/Catalog, Shared Services, and other areas to identify high-value AI and automation opportunities.
Lead discovery workshops, process reviews, and current-state / future-state workflow design sessions with business teams. Translate ambiguous business problems into clear use cases, requirements, controls, success metrics, and implementation plans.
Work closely with IT, data, security, AI platform resources, vendors, offshore or remote technical resources, and business users to ensure solutions are practical, secure, supportable, documented, and aligned with enterprise standards.
Define business requirements, acceptance criteria, approval steps, escalation paths, human-in-the-loop expectations, testing expectations, adoption plans, and benefit measurement for approved automations.
Support AI literacy, power-user enablement, training, change management, and adoption so teams can identify, use, and sustain AI-enabled workflows responsibly.
Track adoption, performance, quality, productivity impact, cost avoidance, service improvement, and realized ROI for deployed solutions.