Shared Services

Enterprise AI Portfolio Lead

Nashville, TN

At a minimum, you will have:

  • 5+ years of experience in business transformation, consulting, product management, operations, technology implementation, or related field.
  • Experience translating business needs into requirements, process maps, user stories, project briefs, or implementation plans.
  • Demonstrated ability to work across business and technical teams.
  • Strong business acumen and ability to connect technology initiatives to measurable business value.
  • Proven ability to complete projects that require multiple stakeholders from different departments and coordination.
  • Ability to overcome internal and external obstacles efficiently with a collaborative mindset.
  • Ability to operate in ambiguity and bring structure to undefined problems.
  • Strong communication skills, including the ability to simplify complex topics for executive and business audiences.
  • Working knowledge of AI, automation, analytics, and emerging technologies.

Determining compensation for this role (and others) at Highspring depends upon a wide array of factors including but not limited to the individual’s skill sets, experience and training, licensure and certifications, office location and other geographic considerations, as well as other business and organizational needs. With that said, as required by local law, Highspring believes that the following salary range reasonably estimates the base compensation for an individual hired into this position in geographies that require salary range disclosure to be between the range below. The individual may also be eligible for a variety of bonus and financial incentives based on individual and company performance.

Base Compensation Range
$110,000—$160,000 USD

Overview

Highspring is looking for an AI leader to help turn AI opportunity into measurable business impact. This role will serve as the connective tissue between business leaders, functional teams, technology partners, and development resources to identify, prioritize, define, and coordinate the implementation of AI-enabled solutions.

This role will bring structure and momentum to our internal AI efforts. The Enterprise AI Portfolio Lead will manage the intake and prioritization of AI use cases, define business requirements and success criteria, coordinate cross-functional delivery, and help ensure solutions are adopted, measured, and scaled appropriately.

The ideal candidate for this role is a hands-on business-minded transformation leader who can operate in ambiguity, ask the right questions, translate business needs into clear requirements, and partner effectively with technical teams to move solutions from idea to implementation.

Responsibilities

AI Use Case Intake and Portfolio Management

  • Establish and manage a centralized process for evaluating internal AI opportunities across the business
  • Maintain visibility into AI pilots, active builds, and proposed use cases across teams
  • Partner with business and functional leaders to understand opportunities, pain points, workflow gaps, and desired outcomes
  • Run the operating cadence of an AI steering group by preparing materials, recommendations, prioritization inputs, and decision points
  • Establish AI governance: usage standards, data and IP safeguards, and build vs. buy decisioning in partnership with IT

Business Requirements and Solution Definition

  • Translate broad AI ideas into clearly defined use cases, business requirements, user stories, workflow maps, and success criteria
  • Define minimum viable pilots and phased implementation plans to test, learn, and scale responsibly

Prioritization and Roadmap Development

  • Develop and maintain a prioritization framework for internal AI initiatives based on business value, feasibility, data readiness, risk, scalability, strategic alignment, and resource requirements
  • Recommend which use cases should be prioritized for pilot, rollout, discovery, or deprioritization
  • Build and maintain a roadmap of initiatives, including timelines, owners, dependencies, and expected outcomes
  • Track progress, risks, blockers, decisions, and dependencies across the AI portfolio

Cross-functional Delivery Coordination and Measurement

  • Serve as the bridge between business stakeholders, IT, data teams, technology vendors, security, operations, and functional owners
  • Coordinate discovery, requirements, development, testing, feedback, launch, and post-launch optimization for approved initiatives
  • Define success metrics for each initiative before build begins, including adoption, time savings, quality improvement, revenue impact, cost reduction, risk reduction, or employee experience outcomes.
  • Monitor adoption and performance after launch and recommend improvements, expansion, or sunsetting when appropriate.
  • Help build organizational confidence in AI by focusing on practical, measurable, high-value use cases.