Sr. Manager, AI Enablement & Adoption, AI.x

Charles Schwab Inc.•Austin, TX

1d•$150,000 - $220,000•Onsite

About The Position

At Schwab, you will build a rewarding career while making a difference in the lives of our millions of clients. Here, innovative thinking meets creative problem solving as we work together to challenge the status quo. We believe in the power of collaboration and value being together in the office, which is why this role is based on-site in our Austin, TX or San Francisco, CA locations. Joining Schwab means joining a company committed to transforming the financial industry and putting clients at the center of everything we do. At Schwab, you are empowered to make an impact on the future of work. Within the AI Strategy & Transformation (AI.x) organization, we are shaping how artificial intelligence becomes embedded in how work gets done across the firm. The Senior Manager, AI Enablement & Adoption is a highly visible, senior individual contributor role responsible for driving meaningful, sustained adoption of AI across Schwab’s internal workforce. This is not a traditional change management or training role. It is an internal operating and integration role focused on translating AI capabilities into everyday productivity, workflow transformation, and measurable business value. You will bring strong technical fluency combined with business judgment and an operational mindset. You will build deep relationships across business units, identify role-based and workflow-based opportunities for AI, and drive them from early adoption through scaled, business-as-usual integration. You will be able to determine what to prioritize, how to sequence change, and what both technology and people need to successfully adopt new ways of working. This role reports to the Director of AI Strategy & Enablement and serves as a connective layer between business leaders, technology teams, and across internal business units. As a seasoned individual contributor, you will help define Schwab’s employee-facing AI adoption journey and ensure investments are intentional, sequenced, and grounded in ROI.

Requirements

Bachelor’s degree or equivalent practical experience.
8–12+ years of experience in technology enablement, digital transformation, product, strategy, internal consulting, or related fields.
Demonstrated experience working closely with data analysis and insights to inform prioritization, measure adoption, and assess business impact.
Strong technical fluency with AI technologies, including large language models and AI platforms.
Proven ability to prioritize initiatives based on value, operational impact, feasibility, and data‑driven insights.
Demonstrated success influencing and aligning stakeholders without direct authority.
Strong communication skills and the ability to engage both senior leaders and frontline teams.

Nice To Haves

Experience operating in large, complex, and regulated organizations.
Background in program management, product management, enterprise technology strategy, or internal business development.
Experience scaling AI or advanced technology use cases from pilots into sustained adoption.
Familiarity with organizational change, workforce transformation, or learning strategies tied to technology adoption.
MBA or advanced degree in business, technology, or a related field.

Responsibilities

Define and execute Schwab’s internal AI enablement and adoption strategy, evolving from early experimentation to scaled, operationalized workflows. Translate AI strategy into practical, role-based and workflow-based adoption plans that fit how employees actually work.
Build and sustain a strong network of AI Champions and business partners across functions. Partner with leaders to identify, shape, and prioritize AI opportunities that drive productivity, quality, risk reduction, and employee experience outcomes. Act as a trusted advisor to business leaders on where AI creates the most value and what it takes to realize it.
Identify high-impact AI use cases with a strong bias toward operational and foundational workflows. Assess opportunities based on value, feasibility, adoption complexity, and scalability. Drive the transition from pilots to repeatable, enterprise-ready solutions.
Partner closely with engineering, product, governance, and vendors to inform AI platform and LLM roadmaps. Ensure technology investments align to adoption needs and measurable outcomes. Maintain technical fluency to bridge business needs with AI capabilities without requiring hands-on engineering.
Lead the human side of AI adoption, including behavior change, trust building, and overcoming adoption friction. Design enablement approaches that go beyond training and focus on embedding AI into day-to-day workflows. Partner on reskilling and upskilling strategies to prepare employees for sustained AI-enabled work.
Operationalize foundational AI-powered workflows so they can scale consistently. Define success metrics, adoption signals, and value indicators. Use data to continuously refine prioritization, sequencing, and enablement strategies.