AI Transformation & Ops Innovation Director

Bunzl Distribution NA•Danvers, MA

About The Position

The Director, AI Transformation & Ops Innovation will work directly with managers across the business to identify opportunities to modernize the organization through AI and lead the successful implementation of those solutions.

Requirements

High school diploma or GED equivalent required
Bachelor’s degree in business, Engineering, Operations, Computer Science, Data Science, or a related field
Demonstrated experience leading AI or digital transformation at an operations-intensive company — manufacturing, distribution, field services, industrial, or similar
Deep operational fluency: you understand procurement, logistics, scheduling, customer service, and shopfloor or field operations well enough to design process improvements, not just recommend them
Demonstrated success partnering directly with frontline managers and operational teams to drive meaningful, on‑the‑ground results
Working knowledge with AI and automation tools: workflow automation platforms, AI-assisted analytics, LLM-based productivity tools, and data integration approaches-the ability to design and refine sophisticated prompts that produce reliable, business-grade outputs
Extensive experience sourcing, evaluating, and managing external vendors and specialized partners for large‑scale technology and transformation initiatives, ensuring accountability for measurable outcomes rather than merely completed deliverables
Strong project management capabilities, with a proven ability to lead multiple concurrent cross‑functional workstreams
High level of maturity and confidence necessary to interact with sophisticated internal and external clients
Strong leadership and customer service skills with the ability to ensure that a high level of service and quality is maintained
Product knowledge with clear technical understanding of services to be able to effectively communicate to customer
Outstanding attention to detail, flexibility and creativity
Persistence coupled with the ability to communicate effectively with individuals at all levels of the organization
Ability to exercise discretion and good judgment, work with minimal supervision and maintain confidentiality of shared information and/or assignments

Responsibilities

Partner with managers across company to map current processes and identify the highest-value AI modernization opportunities
Develop a company-wide AI improvement roadmap, sequenced by impact, feasibility, and strategic priority
Translate business problems into specific AI solutions-from workflow automation to predictive analytics to intelligent customer interaction
Equip employees at all levels with the skills and confidence to use AI tools and models effectively in their day‑to‑day work
Identify specific ways AI can improve an employee’s daily work, remove friction, reduce repetitive tasks, and create time for higher-value activity
Develop AI literacy across all functions, ensuring the organization builds sustainable, distributed capability rather than relying on any single individual
Serve as a true change agent, guiding managers and teams from established, familiar ways of working to AI‑enabled processes through a combination of empathy, patience, and a focus on measurable results.
Address hesitation and resistance constructively by recognizing that concerns about job impact, limited familiarity with AI, and day‑to‑day operational pressures are legitimate barriers—and approaching them as challenges to solve collaboratively rather than obstacles to dismiss.
Monitor adoption, measure outcomes, and continuously refine the transformation approach based on evidence of what is working, using early wins to build confidence and momentum across the organization.
Lead the development of complex AI initiatives to include designing and refining sophisticated prompts and AI workflows that deliver reliable, high-quality outputs for specific business functions
Lead hands-on implementation of AI tools and process changes with each team; stay engaged through adoption and refinement
For complex AI transformations, identify and source the right external partners, vendors, and specialist resources — evaluating options with a clear-eyed view of fit, cost, and delivery risk
Manage external resources end-to-end; hold partners accountable to timelines, quality standards, and business outcomes that benefit the company and it’s customers
Ensure that major initiatives are implemented in ways that transfer knowledge internally to build lasting capability rather than ongoing dependency on outside support
Collaborate with Sales and Marketing on AI-powered tools including the ICP targeting system, lead scoring, pipeline analytics, and customer communication automation already in early deployment
Support initiatives with data infrastructure and analytics that underpin the company’s next-generation value proposition