Director, AI Transformation

Univar Solutions•Downers Grove, IL

4d•$180,000 - $210,000•Hybrid

About The Position

The Director, AI Transformation leads the value and governance engine that turns enterprise AI initiatives into verified, measurable financial impact. Reporting to the Senior Director, Transformation, this role owns day-to-day accountability and sign-off for value certification and AI governance across the portfolio. The role sits between the company's value delivery and technology enablement organizations. It ensures that every initiative with verified financial value is shaped into a deliverable project, properly governed, and made enterprise-ready before it scales, so technology investment stays tied to proven business value and promising ideas convert into measured results. This is a high-impact role that delivers through existing AI, data, engineering, and IT teams. Univar Solutions is backed by Apollo, and this role supports execution of the company's enterprise value creation plan.

Requirements

Bachelor’s degree required; advanced degree (MBA or a quantitative field) preferred.
10+ years in finance transformation, value realization, transformation, or AI and digital program management, including direct ownership of benefits tracking or business-case certification.
Demonstrated ability to certify financial value, including building and defending value cases and underwriting savings with Finance.
Strong command of governance, accountability frameworks, risk and controls, and responsible-AI or data-governance practices.
Track record turning prioritized opportunities into scoped projects and enterprise-grade charters.
Experience coordinating across IT, data, and centers of excellence without direct reporting authority, leading through influence.
Vendor and contract management experience, including statements of work, pilots, and master agreements, in a technology or consulting context.
Executive-grade communication and data storytelling, with comfort presenting value and risk to C-level executives and investors.
Experience in a private-equity-backed transformation or value creation environment.
Working fluency with enterprise AI and data platforms and the economics of scaling AI from pilot to production.
Chemical distribution, industrial distribution, or comparable B2B sector exposure.
CPA, MBA, or equivalent analytical credential.

Responsibilities

Own the value scorecard as the single source of truth for realized savings and EBITDA and cash impact across the AI portfolio.
Run the finance-verified benefits process and provide go/no-go value certification at each stage gate, the authority that determines whether an initiative may scale.
Set and maintain KPI and value-attribution methodology in partnership with Financial Planning & Analysis (FP&A), ensuring every claimed dollar is underwritten by Finance before scaling.
Produce actual-versus-target value reporting for monthly transformation reviews and executive and investor reporting cycles.
Partner with the AI intake and delivery function to convert prioritized, high-value use cases into scoped transformation projects.
Build enterprise-grade charters covering problem statement, value levers, expected dollar impact, success metrics, and 30/60/90-day milestones.
Translate current-state processes, observations, and pain points into clearly scoped opportunities that deliver measurable value.
Sequence and resource the resulting project portfolio so value is delivered on schedule.
Own the value and cost analysis underpinning buy, build, or blend technology decisions, building the financial case behind each recommendation.
Serve on the core decision team that validates recommendations before they advance to executive leadership.
Ground every recommendation in certified value and a credible cost basis.
Serve as the value sign-off in the enterprise go/no-go deployment decision, confirming ROI, hard-EBITDA impact, and cost-per-outcome measures are validated before any initiative deploys or scales.
Ensure every initiative in the AI portfolio clears its required governance, security, legal, and privacy reviews before scaling, working within the enterprise governance framework rather than duplicating it.
Partner with Data Governance, the Center of Excellence, Legal, and Security to drive open risk and readiness items to closure early, so initiatives are not blocked late in the lifecycle.
Escalate items requiring executive sponsor or CIO decision rights, and maintain clear visibility into which initiatives are cleared, conditioned, or held.
Serve as the day-to-day liaison to the AI Center of Excellence and AI engineering teams to avoid duplication and drive reuse of platforms, models, and automation frameworks.
Own the enterprise-readiness criteria that gate broad rollout once a pilot clears its value gate, including hardening, integration, enterprise data, and post-launch stabilization.
Manage clean handoffs across the lifecycle, from framing to pilot to scale-up and stabilization to steady-state business ownership.
Ensure solutions transition to full business unit ownership within the target window, embedded in standard operating procedures and performance metrics.
Own operational vendor relationship management across the AI portfolio, including scoping, statements of work, pilot terms, and commercial follow-through.
Maintain a single, current view of vendor scope, cost, and status across the program.
Partner with Legal, Procurement, and Security on contract review, data terms, and threat scanning for third-party AI tooling.
Surface cost-versus-value exposure on vendor engagements early, such as pilot cost escalations, so they reach value and budget owners before commitment.