Manager, AI Product Management

Acosta•Lewisville, TX

About The Position

The AI Product Management Manager will lead the Brand Advocacy Solutions (BAS) AI product portfolio and a team of AI Product Managers responsible for bringing innovative AI solutions from concept to adoption, commercialization, and long-term business value. Serving as the primary business-facing AI products leader, this individual will partner with the AI Center of Excellence, technology teams, vendors, agency leaders, and cross-functional stakeholders to identify opportunities, evaluate solutions, and scale technologies that solve meaningful business challenges. The ideal candidate brings strong product management and people leadership experience, coupled with a passion for emerging AI capabilities such as Copilot, agentic AI, automation, and productivity platforms. Success in this role requires translating complex technologies into practical, user-friendly solutions while driving governance alignment, stakeholder engagement, product adoption, and measurable business outcomes. Ultimately, this leader will help accelerate innovation across BAS by enabling teams to work smarter, improve efficiency, and realize greater value from AI-powered technologies.

Requirements

Bachelor's degree in Business, Product Management, Information Technology, Computer Science, Marketing, Communications, Operations, or a related field.
5 or more years of experience in product management, technology programs, business operations, digital products, AI, automation, analytics, change enablement, or related roles.
Prior experience leading, coaching, or directly managing product managers or other technology-focused professionals.
Experience managing a portfolio of products or initiatives across different lifecycle stages, including evaluation, development, pilot, launch, adoption, and ongoing optimization.
Demonstrated ability to manage product roadmaps, stakeholder requirements, prioritization, launch planning, adoption activities, and product performance reporting.
Strong business and financial acumen, including business case development, ROI analysis, cost tracking, pricing or packaging inputs, and value-realization reporting.
Working knowledge of responsible AI, data privacy, security, vendor risk, governance, and compliance considerations for enterprise AI products.
Excellent communication and presentation skills, with the ability to translate technical concepts into clear business value and practical direction for internal and customer-facing audiences.
Proven ability to coordinate complex cross-functional work across technology, business, marketing, finance, legal, procurement, vendors, and leadership without direct authority.
Ability to travel occasionally, up to 10%, to support business meetings, workshops, training events, conferences, customer engagements, and organizational initiatives.
Working knowledge of enterprise AI technologies and product patterns, including generative AI, large language models, AI agents, retrieval-augmented generation (RAG), APIs, multimodal AI, prompt design, model evaluation, and AI-enabled workflow automation.
Ability to collaborate effectively with engineering, architecture, data, and security teams without requiring hands-on software development expertise.

Responsibilities

Manage, coach, and develop two AI Product Managers; set priorities and expectations; allocate products and initiatives across the team; provide regular feedback; support career development; and create clear accountability for deliverables, decisions, stakeholder engagement, and product outcomes.
Identify and evaluate emerging AI capabilities, technologies, vendors, and use cases that can improve business operations, employee productivity, field execution, customer experiences, or create new commercial opportunities. Lead discovery, experimentation, prototypes, and pilots; evaluate build, buy, or partner approaches; and recommend which opportunities should scale, evolve, or stop.
Oversee the BAS AI product portfolio and establish consistent product management practices across products that may be live, in development, in pilot, or under evaluation. Maintain portfolio visibility, priorities, roadmaps, dependencies, lifecycle status, investment needs, risks, and leadership reporting.
Guide product strategy, business requirements, roadmaps, enhancement backlogs, feature prioritization, release planning, adoption targets, utilization, business outcomes, customer feedback, and product health. Ensure each product has clear ownership, success measures, and an actionable path to value realization.
Lead intake and evaluation of AI opportunities; assess strategic fit, business value, feasibility, cost, risk, stakeholder readiness, dependencies, data availability, quality, accessibility, ownership, integration requirements, and data readiness; recommend priorities; and coordinate handoffs and decisions across business, technology, governance, and delivery teams.
Partner with the AI Center of Excellence, IT, Security, Privacy, Legal, Procurement, and business stakeholders to support responsible AI reviews, data governance, third-party risk, security, compliance, contracting, and lifecycle controls. Ensure product decisions and releases align with organizational standards and approved use cases.
Develop and review business cases, ROI analysis, pricing and packaging inputs, commercialization approaches, cost models, and value-realization reporting. Track relevant costs such as licensing, token and API usage, cloud infrastructure, vendor fees, and ongoing support needs.
Set the portfolio approach for product positioning, launch readiness, training, user guidance, champion networks, demos, stakeholder updates, executive reporting, and adoption campaigns. Ensure communications clearly explain the use case, target audience, expected value, support model, and responsible-use expectations.
Lead product and vendor reviews, roadmap discussions, evaluations, open issues, enhancement requests, renewals, and escalations in partnership with Procurement, Legal, IT, Finance, Marketing, agency leaders, and business stakeholders. Build strong relationships and influence outcomes without direct authority.
Establish and monitor portfolio and product KPIs across adoption, efficiency, quality, business impact, and user satisfaction. Establish appropriate AI-specific evaluation measures, including accuracy, quality, reliability, latency, cost, human intervention requirements, responsible-AI performance, and other use-case-specific measures. Identify performance gaps, support trends, product friction, and opportunities for improvement; provide recommendations and concise status updates to leadership and stakeholders.