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Executive Director, AI Enterprise Process & Innovation

Job in Charleston, Charleston County, South Carolina, 29408, USA
Listing for: Astrazeneca
Full Time position
Listed on 2026-01-22
Job specializations:
  • IT/Tech
    AI Engineer, Business Systems/ Tech Analyst, Data Scientist, Data Analyst
Job Description & How to Apply Below

Are you ready to rewire how a global enterprise operates—embedding AI where decisions are made—to accelerate how life-changing medicines reach patients? In this role, you will set direction in the earliest stages, turning uncertainty into clarity and building decision-centric operating models that remove latency and unlock scale.

You will lead a cross-company transformation that brings business, technology, data, and change capabilities together to deliver tangible outcomes. Your work will connect R&D, Manufacturing, Quality, Commercial, Medical, Legal, Finance, and Procurement into seamless, intelligent workflows that improve quality, speed, and efficiency. Can you turn ambiguous opportunities into scaled operating leverage across the enterprise?

Accountabilities

Redesign critical end-to-end processes to move from functionally optimized workflows to decision-centric models. Embed AI at the point of work. Eliminate structural bottlenecks, manual handoffs, and decision delays to develop intelligent, streamlined operations that improve patient impact.

Act as a cross-functional integrator by incubating and scaling AI-enabled use cases across functions. Develop consistent processes to move ideas from pilot to scaled enterprise capability that delivers measurable business value.

Advisory Role within the Organization and Value Realization:
Partner with senior leaders to compose problem statements, outline benefit scenarios, and align AI solutions with business outcomes. Collaborate alongside Finance and enterprise leaders to develop metrics, track benefits, and confirm return on investment. Advise on areas where AI impacts operating leverage compared to where traditional optimization meets needs.

Collaborate with AI, data, technology, risk, quality, and legal/compliance teams to ensure solutions are scalable, secure, compliant, and ethical. Codify governance that speeds delivery without compromising safety or trust.

Lead adoption using innovative operational methods. Redefine roles and improve decision-making accountability. Build enterprise understanding of AI through leadership narratives, education, and hands‑on engagement. Develop talent and communities of practice passionate about process innovation, AI product thinking, and system development. Plan effectively for succession.

Lead or coordinate complex, high-value AI‑enabled business improvement initiatives. Orchestrate cross‑functional squads to remove blockers and embed AI into daily operations. Socialize strategic outcomes by demonstrating cost, quality, and financial improvements.

Essential Skills/Experience
  • Lead the redesign of important enterprise processes across the entire workflow. Transition from workflows optimized for functionality to AI‑enabled, decision‑focused operating models. Identify structural bottlenecks, manual handoffs, and slow decision points. Build intelligence into workflows rather than layering additional tools.
  • Serve as an integrator across functions by connecting business, technology, data, and change capabilities to achieve enterprise‑wide innovation. Incubate and expand AI‑enabled use cases in areas such as R&D, Manufacturing, Quality, Commercial, Medical, Legal, Finance, and Procurement. Develop repeatable methods to progress ideas from pilot to broad organizational capability.
  • Internal Consultancy & Value Realization:
    Operate as a strategic internal consultancy to senior business leaders, shaping problem statements, defining value cases, and aligning AI solutions to business outcomes; partner with Finance and business owners to define clear value metrics, track benefits realization and ROI, and ensure sustained impact; advise executives on where AI can change operating leverage vs. where traditional optimization is sufficient.
  • AI Operating Model & Governance:
    Partner with Enterprise AI, Data, IT, Risk, Quality, Legal/Compliance and GBS to ensure AI solutions are scalable, secure, compliant, and ethically deployed.
  • Change Leadership & Capability Building:
    Drive adoption through new ways of working, role redesign, and decision accountability—not just technology deployment; build enterprise understanding of AI’s role in…
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