Head of AI Acceleration

Dexter; Novi (MI); Hybrid; USD 180,000 - 240,000; Full time

Job summary

DexKo is seeking a Head of AI Acceleration to drive AI strategy execution and adoption across the organization. You will align business units, technical teams, and stakeholders to move AI initiatives from idea to production with measurable business impact.

The role requires leading across the enterprise to accelerate AI delivery, establish governance, and ensure consistent, scalable execution. Travel up to 25% and matrixed environment experience are valued.

Qualifications

• Proven ability to design and drive enterprise AI programs across multiple business units.
• Strong track record of delivering measurable business outcomes through AI initiatives.
• Fluency in AI, data, and analytics with ability to translate technical concepts to business leaders.
• Experience operating in a matrixed organization and coordinating with diverse teams.

Responsibilities

• Drive AI adoption and business impact by embedding AI into workflows and decisions.
• Shape and execute a prioritized AI roadmap aligned with enterprise strategy.
• Build organizational capability through partnerships, enablement, and governance.
• Lead end-to-end AI execution across idea, business case, POC, to production.
• Orchestrate a federated AI model with clear ways of working across networks.
• Establish standards, governance, and scalable ways of working for AI delivery.
• Provide leadership visibility with clear pipeline, progress, and impact reporting.

Skills

AI strategy

Cross-functional leadership

Program management

Stakeholder alignment

Change management

Job description

Overview

The Head of AI Acceleration is responsible for driving AI strategy execution and adoption across DexKo. This role drives the enterprise AI direction and ensures initiatives move from idea to production at speed, delivering measurable business impact. This leader works across business units, technical teams, and functional stakeholders to align priorities, remove barriers, and ensure consistent, scalable execution of AI initiatives. This role is accountable for orchestrating efforts across the organization to accelerate progress and outcomes. As AI resources are distributed across the company, this role will need to coordinate and influence resources in other business functions and segments.

Responsibilities

Drive Adoption and Business Impact

• Ensure AI solutions are not just built, but adopted and embedded into how work gets done
• Partner with business leaders to define changes in roles, processes, and decisions as a result of AI initiatives
• Establish adoption, usage, and impact metrics across all initiatives
• Monitor performance and drive continuous improvement post-deployment

Shape And Execute AI Roadmap

• Translate enterprise strategy into a prioritized, actionable AI roadmap
• Balance quick wins with longer-term, high-impact initiatives
• Continuously refine priorities based on business needs and results

Build Organizational Capability

• Support the development of AI capability across the business through AI Business Partners, Training and enablement programs, and communication.
• Foster a culture of experimentation, learning, and responsible AI use

Drive Enterprise AI Execution

• Collaborate with business, CoE, and external partners on the end-to-end execution of AI initiatives through the pipeline (idea ? use case ? business case ? POC ? implementation ? production)
• Ensure initiatives progress at pace, with clear accountability and measurable outcomes
• Identify and remove barriers to execution across teams and functions
• Apply company-wide value stream lens to portfolio of projects to ensure holistic approach and project connectivity across business processes, functions, segments and geographies

Orchestrate a Federated AI Model

• Align and coordinate across: Central AI / technical resources and CoE, Business Unit AI Business Partners, Business analysts and AI stewards embedded in functions
• Establish clear ways of working across this network to ensure consistency and efficiency
• Drive prioritization across competing initiatives and resources

Standards, Governance, and Ways of Working

• Collaborate with and provide feedback to CoE and AI Governance Council regarding standards for: Use case development, Business case rigor, Model deployment and lifecycle management, change management, ROI and benefit tracking
• Partner with governance bodies (e.g., AIGC) to ensure appropriate controls without slowing progress
• Ensure a repeatable, scalable approach to AI delivery

Provide Visibility To Leadership

• Deliver clear, concise reporting to ELT and stakeholders on:
• Pipeline status
• Initiative progress
• Business impact
• Risks and dependencies
• Create transparency and accountability across the AI portfolio

Key Interfaces

• Chief Business Strategy & Transformation Officer
• Business Unit Leaders
• AI Business Partners (dotted-line alignment)
• Central AI / Data / Technology teams
• Functional leaders (Operations, Finance, Purchasing, etc.)

Success In This Role Will Result In The Following

• AI initiatives consistently move from idea to production without stalling
• Clear visibility into pipeline, priorities, and impact across the enterprise
• Strong alignment between business units and technical teams
• Measurable business value delivered at increasing scale
• AI becomes embedded in how work is done—not isolated pilots

Qualifications

Ideal Attributes

• Execution-focused: drives outcomes, not just strategy
• Influential: able to lead without direct authority
• Pragmatic: balances speed with structure
• Credible: trusted by both business and technical stakeholders
• Resilient: able to push through resistance and ambiguity

Experience & Knowledge

Years of experience: 7-15 years

• Proven experience leading large-scale, cross-functional initiatives in a complex organization
• Strong track record of driving execution and delivering measurable business outcomes
• Experience working across business and technology teams
• Familiarity with AI, data, and advanced analytics (deep technical expertise not required, but strong fluency expected)
• Experience operating in a matrixed model

Working Conditions

• Travel frequency: Up to 25%