SupplyHouse.com - Director of Enterprise AI Adoption

• AI Strategy and Roadmap • Develop and own the enterprise AI adoption strategy aligned with SupplyHouse's business objectives and long-term growth plans. • Identify high-impact AI use cases across procurement, operations, sales, customer service, and finance, and prioritize based on ROI and feasibility • Serve as the primary internal authority on enterprise AI tools, platforms, and best practices including large language models, agentic workflows, and AI-powered analytics • Monitor the AI technology landscape and advise executive leadership on emerging opportunities and risks • People, Change Management, and Culture • Design and execute enterprise-wide change management programs grounded in proven methodologies to drive sustained, high-quality AI adoption across all levels and functions • Act as a culture carrier for AI transformation championing a mindset of curiosity, continuous learning, and responsible experimentation throughout the organization • Build internal champions, AI ambassadors, and center-of-excellence structures to scale AI literacy and usage across every business unit • Develop training curriculum, playbooks, and role-based enablement programs to upskill employees on AI tools and workflows at every level, from frontline staff to senior leadership • Create psychological safety around AI adoption by proactively addressing employee concerns about job displacement, skill gaps, and the pace of change positioning AI as a tool that augments human capability rather than replaces it • Partner closely with the Human Resources team to embed AI competency into hiring profiles, onboarding programs, performance frameworks, and career development pathways • Lead executive communications, all-hands presentations, and town halls related to AI strategy, adoption milestones, and organizational impact • Identify and mitigate human-side risks of AI adoption including change fatigue, resistance patterns, and inequitable access to enablement resources across teams • Cross-Functional Leadership • Partner with department heads across IT, Operations, Human Resources, Legal, and Finance to embed AI into core business processes • Collaborate with the IT and Data Engineering teams to ensure secure, compliant, and scalable AI infrastructure • Manage relationships with external AI vendors, consultants, and technology partners • Coordinate with Legal and Compliance teams to establish responsible AI governance policies, data privacy standards, and risk frameworks • Measurement and Optimization • Define KPIs and success metrics for AI adoption initiatives and report progress to the C-suite and Board as needed • Establish feedback loops and continuous improvement processes to optimize AI tool performance and user experience • Build business cases and ROI models to justify AI investments and scale successful pilots enterprise-wide • Team Leadership • Team Leadership • Build, lead, and mentor a high-performing team of AI program managers, analysts, and change agents • Foster a culture of experimentation, curiosity, and responsible innovation within the team and across the organization • SupplyHouse is a people-first company with deep roots in the trades. We move fast, but we bring our teams along with us. The ideal candidate for this role is not just a technologist – they are a trusted colleague, a patient teacher, and a relentless advocate for making AI work for everyone, not just the tech-savvy individuals. You will succeed here if you: • Lead with empathy and communicate change in ways that resonate with frontline workers and executives alike • Are comfortable with ambiguity and energized by building something new in an organization that is still defining what AI means for its people • Believe that culture and adoption are the hardest, and most important, parts of any technology transformation • Listen before you prescribe, and take the time to understand the unique needs, fears, and motivations of each team you partner with • Bring optimism and patience to resistance, treating skepticism as useful signal rather than an obstacle • Hold yourself and your team accountable to outcomes, not just outputs (e.g.: adoption rates, workflow efficiency, and employee confidence matter more than tools deployed)