Program Manager - AI Transformation & Workforce Strategy

Program Manager - AI Transformation & Workforce Strategy Role intent: Be the transformation engine that helps Schneider Electric anticipate, adopt and scale agentic AI across software product engineering work, skills, teams, economics and operating models. About Schneider Electric and the transformation Schneider Electric is accelerating the transformation of Energy Management through software, services, digital capabilities and AI-powered innovation. Within Energy Management, the Software & Services Division brings together a large global software product engineering population and plays a central role in shaping the next generation of connected, intelligent and software-defined offers. Generative AI and agentic AI are now reshaping how software is designed, developed, tested, secured, operated and continuously improved. The opportunity is broader than individual productivity: it requires rethinking software product engineering workflows, team composition, skills, career paths, governance, economics and value realization. To address this strategic shift, Schneider Electric is launching a transversal program hosted in the Software & Services Division, with a mandate to understand and anticipate the impact of agentic AI on software product engineering jobs and ways of working across Energy Management. The program will be supported by BCG and sponsored by the Software & Services CTO leadership. The opportunity We are seeking a strategic and execution-oriented transformation leader to establish and drive Schneider Electric's AI Transformation and Workforce Strategy agenda for software product engineering. This role will act as the central orchestrator of a multi-year transformation across technology, people, operating model and value realization. The successful candidate will work closely with CTOs, engineering leaders, product leaders, HR, Schneider Digital, Finance and external partners (consultants) to move the organization from AI-assisted development toward AI-enabled and agentic software product delivery. The role requires the ability to connect technology strategy with workforce transformation: understanding how software product engineering work changes, how teams evolve, which capabilities need to be built, what value is created, and how adoption can be scaled sustainably across a diverse global software product engineering population.

1. Define the future of AI-powered software product development lifecycle at Schneider Electric (inputs from EM CTO, S&S CTO, Strategy teams) Contribute to develop and operationalize the vision, ambition and roadmap for AI-powered software product engineering across Energy Management. Assess how Generative AI and agentic AI will reshape software product engineering work, team structures, governance, decision rights and workforce requirements. Translate external technology trends and benchmarks into pragmatic transformation choices for Schneider Electric. Support executive recommendations on future software product engineering operating models, including maturity stages from AI-assisted development to agentic and autonomous delivery models. 2. Orchestrate the workforce transformation Map the baseline of software product engineering roles, skills, capabilities, personas and team structures. Identify roles and activities that will be augmented, recombined, created or significantly redesigned as AI adoption matures. Partner with leaders and HR to build workforce scenarios, talent implications and capability development plans. Define upskilling and reskilling pathways for software product engineers, architects, technical leads, engineering managers and product roles, while leveraging the internal resources (Schneider Digital, Digital Academy) Anticipate impacts on career paths, recruiting needs, talent segmentation and future workforce planning. Identify & empower AI champions in current teams to become trainers of next enablement waves 3. Accelerate AI adoption across software product engineering teams Design and execute adoption programs that move beyond tool access and training to sustained changes in software product engineering behaviors and workflows. Lead pilot teams, adoption sprints and scaling approaches, including squad-by-squad activation where relevant. Create repeatable playbooks for AI adoption, maturity progression, leadership activation and local change networks. Build a clear change narrative by persona, including “what is in it for me” for software engineers, product managers, software product engineering leaders and HR stakeholders, leveraging company/EM position papers and narrative. Ensure adoption efforts measure depth and breadth of usage, not only license activation or superficial tool engagement. 4. Drive value realization and transformation economics Define and operate a robust measurement framework covering adoption, productivity, quality, developer experience, workforce impact, cost and business value. Track AI consumption economics, including token usage, tool spend, productivity benefits and return on investment. Build executive dashboards and governance routines to steer decisions, funding allocation and scaling priorities. Translate pilot outcomes into value cases, investment recommendations and scale-up roadmaps. Ensure productivity improvement is balanced with software quality, security, reliability, developer experience and ethical AI guardrails. 5. Shape the future software product engineering operating model Assess how team composition, squad structures and software product engineering practices evolve as AI agents absorb more execution work. Define future collaboration models between software engineers, product managers, architects, testers, AI agents and platform/tooling teams. Support the design of human-in-the-loop and human-over-the-loop models, including escalation, review and accountability principles. Partner with software product engineering leadership to ensure the transformation improves speed, simplicity, predictability and strategic value creation. 6. Lead transformation governance and partner orchestration Establish and operate the transformation office, governance model, steering committee cadence and reporting drumbeat. Coordinate workstreams across Software Engineering, Product, HR, Finance, Schneider Digital, AI platform teams and external partners. Manage the day-to-day interaction with BCG and ensure consulting support translates into Schneider Electric-owned capabilities and outcomes. Prepare executive decision materials, strategic recommendations, progress reviews and communication packages for senior leadership. Act as trusted advisor to the CTO leading the transversal effort and to the executive sponsor. Success after 12 months Measurement & value A baseline assessment of roles, skills, teams, adoption maturity and tool usage is completed for the target software product engineering population, alongside a quantified & syndicated targets Executive dashboards are in place to track adoption depth, productivity, quality, sentiment, value realization and AI consumption economics. Productivity has increased for enabled waves (>20pp of productivity increase) Enablement & adoption A clear AI Product teams transformation roadmap is approved and launched across Energy Management: Pilot adoption sprints are a success and translated into scaling playbooks with measurable impact 3+ enablement waves (~300 person per waves) are done, reaching maturity targets (>60% level 3) Internal trainers have taken over external support Governance & operating model North Star tooling stack confirmed, approval process live, provisioning done. Concrete workforce recommendations are delivered, including reshaped roles, critical skill gaps and capability-building priorities. A sustainable governance model is operating, with clear decision rights, investment priorities and scaling criteria. Qualifications and experience Required 10+ years of experience in technology transformation, software engineering, management consulting, digital transformation, strategy, product/engineering operations or related fields. Proven track record leading complex, cross-functional transformation programs in a global environment. Strong understanding of software product engineering organizations, SDLC, Agile/DevOps practices, developer productivity and software product engineering operating models. Ability to engage credibly with CTOs, senior engineering leaders, product leaders, HR leaders and external partners. Excellent analytical, problem-solving, synthesis and executive communication skills. Demonstrated ability to translate strategic ambition into practical roadmaps, governance, metrics and measurable outcomes. Preferred Experience in a leading strategy consulting firm, technology company, software business, platform organization or CTO office. Exposure to Generative AI, agentic AI, developer tools, AI-enabled SDLC, developer experience or engineering productivity initiatives.