The AI Business Acceleration Manager is a hands-on AI product and enablement leader responsible for identifying and delivering high-impact AI and automation initiatives across the ACL sector.
This role focuses on identifying and documenting AI use cases, developing POCs, and collaborating with the Enterprise AI Governance Council to scale practical AI solutions that improve overall operational efficiency and commercial performance. Working closely with various BU leaders and stakeholders across manufacturing, supply chain, marketing, sales, customer care, and data teams, this individual translates business needs into AI-enabled solutions, focusing on driving measurable results through disciplined execution.
***The ideal candidate will reside within a 3-hour drive of the Harrisburg, PA metro area***
Key Responsibilities
AI Use Case Identification & Delivery
• Identify, validate, and prioritize high-value AI and automation opportunities aligned with ACL sector priorities across CLS, IND, and PTS.
• Translate business challenges into actionable AI and automation initiatives, partnering with data, tech teams, and process owners, as needed, to define solutions.
• Ensure solutions are scalable, practical, and embedded into existing workflows.
• Build business cases and define measurable ROI and success criteria for initiatives.
• Establish a demand management framework to identify and prioritize AI and advanced analytics initiatives.
AI Enablement & Adoption
• Promote responsible and effective use of AI tools such as TELme, Copilot, and ChatGPT Enterprise.
• Lead AI Trailblazer team meetings by demonstrating practical use cases that improve day-to-day productivity and decision-making and establish AI champions across various functions.
• Support AI literacy efforts across ACL sector BUs.
• Track adoption and gather feedback to improve ongoing engagement and AI usage.
• Build and sustain an AI community of practice within the ACL sector to share lessons learned, tools, and best practices.
Cross-Functional Execution
• Partner with functional leaders to prioritize use cases based on value and feasibility.
• Coordinate with data, analytics, tech, and process teams to implement AI solutions.
• Remove blockers and drive progress through structured project management.
• Ensure alignment with enterprise platforms (Salesforce, SAP, Databricks, etc.).
• Lead end-to-end delivery of approved AI use cases from concept through pilot and scale.
Data Readiness to enable AI use cases
• Partner closely with the AI Governance Council to ensure priority use cases across ACL BU’s are presented for solutioning.
• Partner closely with Data & Analytics teams to ensure priority AI use cases have the data access and quality needed for execution.
• Act as the business bridge, translating AI requirements into clear data needs while ensuring compliance with existing governance and security standards.
• Identify data gaps impacting AI use case execution.
• Support creation of curated datasets required for specific AI initiatives.
Performance Measurement
• Define and track KPIs for AI initiatives (revenue impact, productivity gains, cycle time reduction).
• Monitor pilot performance and recommend scaling decisions.
• Document lessons learned and identify reusable assets.
• Stay current on emerging AI tools and technologies.
