Title:  Sr. Director, AI Business Architecture & Enterprise Adoption

Job Summary

Reporting to the CIO, the Sr. Director, AI Business Architecture & Enterprise Adoption will lead NetApp's approach to AI-enabled business transformation — designing the operating model for AI adoption, driving business-side governance, and ensuring measurable value realization across business functions. 

This role partners closely with NetApp's AI Engineering team, which builds and operates the company's enterprise AI Shared-Services platform, along with Application Engineering teams, who own vertically oriented AI capabilities within their respective application portfolios. AI Business Architecture focuses on the demand side of that partnership: driving adoption of the platform across business functions, designing how the business consumes AI, and leading the transformation initiatives needed to turn AI capability into measurable business outcomes. 

This leader partners across business, product, data, security, legal, HR, and finance organizations to convert a growing enterprise AI capability into scaled business transformation. The role combines business architecture discipline with AI adoption leadership: guiding executives through AI-enabled change, connecting business outcomes to available AI capabilities, shaping investment priorities on the adoption side, and ensuring initiatives deliver measurable results. 

As a senior member of the IT leadership team, this leader serves as a trusted advisor to executive leadership on where and how to apply AI across the enterprise. 

Job Responsibilities

AI Enablement Strategy & Transformation 

Define NetApp's AI enablement strategy: how business functions adopt and apply AI capabilities to drive transformation outcomes. 

Develop multi-year adoption and transformation roadmaps connecting available AI capabilities to measurable business outcomes, productivity improvements, and customer value. 

Identify which business processes and functions are best positioned to benefit from existing and emerging AI capabilities, and prioritize where transformation effort should focus. 

Partner with executive leadership to prioritize which business problems get solved with AI, and align transformation initiatives to business value realization. 

Serve as a trusted advisor to senior leaders on AI adoption, business readiness, and transformation sequencing. 

Business Architecture & Strategy-to-Execution 

Guide business leaders through transformation and optimization initiatives that leverage AI, automation, and analytics capabilities. 

Develop business architecture deliverables: business capability models, value stream assessments, operating model designs, business outcome frameworks, and transformation roadmaps. 

Translate enterprise strategy into business capabilities, adoption plans, and executable transformation programs. 

Partner with business and IT leaders to assess opportunities for revenue growth, cost optimization, risk mitigation, customer experience enhancement, and operational excellence. 

Facilitate executive decision-making on transformation priorities, operating model evolution, and AI-enabled ways of working. 

Create clear line-of-sight between strategic objectives, available AI capabilities, and measurable outcomes. 

AI Adoption Operating Model & Portfolio Visibility 

Design the adoption-side operating model: decision rights, intake processes, and prioritization frameworks for business-initiated AI use cases, embedded into existing business funding and planning processes. 

Build and lead a network of embedded AI champions across business functions who translate business needs upward and drive local adoption. 

Create enterprise visibility into business-facing AI use cases, adoption status, business ownership, and expected outcomes. 

Partner with Legal and Risk to define an independent review checkpoint for responsible AI use, covering business impact, privacy, and regulatory exposure. 

Drive consistency in how business functions adopt AI, reducing duplicate or ungoverned AI initiatives across the business. 

Data, AI & Business Capability Enablement 

Partner with data and AI leaders to understand data readiness, governance, and quality constraints that shape what's achievable for business adoption. 

Connect business architecture, adoption planning, and data/AI capability into one enablement framework. 

Identify where predictive AI, generative AI, agentic AI, and intelligent automation can be applied to specific business problems. 

Advise business leaders on how their own data maturity, process maturity, and organizational readiness affect their ability to adopt AI successfully. 

Promote reuse of shared platforms and standardized practices rather than one-off business-unit builds. 

Job Requirements

• 10+ years in business technology leadership, business architecture, digital transformation, product strategy, management consulting, or related disciplines. 
• 5+ years of senior leadership experience influencing executive stakeholders in large, matrixed organizations, including leading through influence over teams and functions outside direct management. 
• Proven ability to connect business strategy, operating model design, and technology capabilities to measurable business outcomes. 
• Experience designing adoption operating models, embedded champion or liaison networks, or federated operating structures. 
• Strong executive communication, facilitation, and stakeholder management skills. 
• Demonstrated experience driving enterprise change and cross-functional adoption programs. 
• Working understanding of AI, automation, and analytics sufficient to have credible technical conversations with engineering leadership.