AI Product Lead

Summary:

The AI Product Lead serves as the bridge between assigned business functions and the AI Center of Excellence. This role identifies high-value business problems, translates them into viable AI and automation products, and leads each opportunity from discovery through pilot, adoption, and measurable value realization.

The AI Product Lead begins with the business problem, not the technology. The role determines whether the appropriate solution is process redesign, traditional automation, generative AI, an AI agent, predictive AI, a purchased product, or no technology solution at all.

This role will support business functions such as HR, Supply Chain, Legal, Marketing, Field Operations Support and Sales Operations.

Primary Responsibilities:

- Build trusted partnerships with functional leaders, process owners, frontline employees, and technology teams.
- Lead discovery workshops to understand business objectives, user needs, process pain points, constraints, and opportunities.
- Translate loosely defined ideas into clear problem statements, business-outcome hypotheses, product requirements, and prioritized roadmaps.
- Establish current-state baselines, including cost, effort, volume, cycle time, quality, risk, and user experience.
- Develop credible business cases covering expected value, delivery cost, resource needs, dependencies, risks, and success measures.
- Define the minimum viable product, user experience, backlog, acceptance criteria, pilot scope, and product roadmap.
- Partner with Applied AI Specialists, solution architects, data teams, automation developers, and platform teams throughout delivery.
- Coordinate required reviews with Legal, Privacy, Cybersecurity, Risk, Compliance, Architecture, and AI Governance.
- Lead user-acceptance testing, controlled pilots, release readiness, adoption, communications, and change enablement.
- Measure product performance and realized benefits, recommending whether to scale, improve, redesign, purchase, defer, or stop.
- Identify reusable capabilities and patterns that can be applied across multiple business functions.

Required Experience and Capabilities:

- Bachelor's degree in Computer Science, Information Systems, Engineering, Analytics, Five or more years of experience in digital product management, intelligent automation, process transformation, technology delivery, or a related discipline.
- Demonstrated ownership of enterprise products or solutions from opportunity discovery through launch, adoption, and value realization.
- Strong product-management capabilities, including product strategy, roadmaps, requirements, user stories, backlog prioritization, MVP definition, and success metrics.
- Experience conducting process discovery and translating business needs into practical technology solutions.
- Ability to develop business cases, quantify benefits, estimate resource requirements, and communicate investment trade-offs.
- Working knowledge of generative AI, AI agents, RPA, workflow automation, APIs, system integration, enterprise data, and cloud-based AI platforms.
- Ability to collaborate effectively with engineering, architecture, data, security, risk, Legal, Privacy, and change-management teams.
- Strong executive communication, workshop facilitation, storytelling, negotiation, and stakeholder-management skills.
- Experience delivering solutions in an Agile or iterative product-development environment.

Preferred Qualifications:

- Experience delivering generative AI, agentic AI, intelligent automation, predictive AI, or enterprise workflow products.
- Familiarity with platforms such as Google Gemini Enterprise, Google Cloud, Microsoft Copilot, Microsoft Azure, UiPath, Salesforce, ServiceNow, or Oracle.
- Experience operating in a regulated or control-intensive enterprise environment.
- Familiarity with responsible AI, data governance, human-in-the-loop controls, model evaluation, privacy, security, and auditability.
- Experience with design thinking, Lean or Six Sigma, process mining, user research, and organizational change management.
- Relevant credentials in product management, Agile delivery, cloud, AI, automation, or process improvement.

Ideal Candidate Profile:

- Business- and outcome-oriented: Starts with the problem, user, and measurable result rather than a preferred AI tool.
- Comfortable with ambiguity: Can create structure from incomplete requirements and immature ideas.
- Technically fluent: Understands AI and automation sufficiently to make informed product decisions and work credibly with technical teams.
- Commercially minded: Understands implementation cost, platform consumption, licensing, internal capacity, and benefit realization.
- Governance-conscious: Integrates privacy, security, responsible AI, human oversight, and controls into product design.
- Hands-on: Personally leads discovery, develops product artifacts, manages the backlog, supports pilots, and resolves delivery issues.
- Adoption-focused: Recognizes that a technically successful solution creates no value unless users adopt it and business processes change.
- Decisive: Can recommend proceeding, redesigning, buying, deferring, or stopping based on evidence.

Measures of Success:

- Quality and strategic alignment of the functional AI and automation pipeline.
- Percentage of opportunities supported by defined owners, baselines, outcomes, and success measures.
- Speed from opportunity identification to validated MVP decision.
- Adoption and user satisfaction for deployed products.
- Financial, operational, risk, and capacity benefits realized.
- Reusable product patterns created across functions.
- Percentage of delivery completed through internal capability versus external implementation dependency.