Head of AI Strategy & Operations Remote

Accela is seeking a Head of AI Strategy & Operations to help teams across the company use AI effectively and responsibly. You will shape our enterprise AI strategy, set practical standards, and guide investments that improve how people work and deliver measurable results.

As Accela becomes an AI-first company, you will help turn that ambition into everyday practices, useful tools, and stronger employee capabilities. You will work with business and technical leaders to set priorities, support experimentation, and give executives a clear view of progress, costs, and risks. Each function will continue to own its workflows and results.

This role combines strategic thinking, practical AI experience, and the ability to bring people together around shared goals. You will work closely with Product, Engineering, IT, Security, Legal, Privacy, GRC, HR, Finance, Procurement, and functional leaders to make responsible AI adoption easier and faster. Functions retain ownership of their workflows, delivery, and outcomes. You own the enterprise strategy, requirements, operating model, and portfolio visibility that help those teams execute consistently.

You will partner closely to align enterprise requirements with operational needs and incorporate evidence from that portfolio into enterprise decisions.

Responsibilities:

• Shape AI strategy. Develop Accela’s enterprise AI strategy and investment priorities. Assess the company’s AI capabilities and readiness, and align plans with business goals, available resources, and acceptable risk.
• Prioritize opportunities. Work with business and technical leaders to identify promising uses of AI. Weigh expected benefits, readiness, data needs, effort, risk, and cost. Define success measures and recommend which initiatives to fund, expand, adjust, or stop.
• Lead AI governance. Establish clear risk categories, review processes, and approval criteria so teams can move forward responsibly and efficiently.
• Set practical requirements. Translate legal, regulatory, contractual, and policy obligations—including those related to government customers—into clear requirements for security, privacy, data use, human oversight, and AI evaluation.
• Clarify ownership and decisions. Define responsibilities and handoffs from early experiments through deployment and retirement. Resolve conflicts between enterprise and functional requirements within your authority, document decisions, and respect existing approval responsibilities.
• Maintain portfolio visibility. Keep a current company-wide view of AI initiatives, approved tools, owners, investments, dependencies, and risks.
• Support employee adoption. Provide training suited to different roles, practical guides, templates, office hours, and peer learning. Build an AI champion network and use employee feedback to make approved tools and practices easier to use.
• Build team capabilities. Partner with functional leaders to address skill gaps, support changing roles, and set AI goals that improve workflows, quality, employee experience, and business results.
• Guide technology choices. Work with Engineering, IT, Security, and other responsible teams to select approved tools, reduce duplication, and develop reusable capabilities. Evaluate when to build, buy, or configure solutions.
• Establish technical standards. Partner with implementation teams on access controls, activity records, monitoring, incident response, and ongoing management of AI systems.
• Test ideas in practice. Use AI-assisted development and targeted prototypes to test assumptions before larger investments. Work closely with teams that build and operate production systems to understand technical constraints and trade-offs.
• Measure results and costs. Build an executive scorecard covering…