AI Transformation & Change Manager

ActiveProspect, Inc.•Austin, TX

About The Position

ActiveProspect is seeking an AI Transformation & Change Manager to lead the practical adoption of artificial intelligence across the company’s non-technical functions. This is a highly hands-on role responsible for identifying high-value opportunities, designing and implementing AI-enabled solutions, managing organizational change, and building AI knowledge and confidence across functional teams. This individual will translate the company’s AI strategy into measurable business outcomes. They will work directly with teams to understand existing processes, challenge the status quo, redesign workflows, deploy solutions, and ensure employees have the training and support necessary to adopt new ways of working. The successful candidate will be both a strategic thinker and a strong executor. This is not a strategy-only or advisory role; the AI Transformation & Change Manager will be expected to personally drive initiatives from opportunity identification through implementation, adoption, and ROI measurement.

Requirements

Hands-on execution and ownership
Strategic thinking with strong operational discipline
Curiosity and continuous learning
Business-process redesign
Change leadership and organizational influence
Stakeholder management and executive presence
Practical problem-solving
Training, coaching, and facilitation
Data-driven decision-making
Sound judgment regarding risk and compliance
Ability to challenge the status quo constructively
Ability to create momentum in an evolving and ambiguous environment

Nice To Haves

Formal change-management certification or framework experience (Prosci / ADKAR or equivalent).
Experience in a high-growth SaaS or private-equity-backed environment, and comfort operating without established process.

Responsibilities

Partner with the CFO and the Vice President of Business Systems, Compliance and IT to develop and execute the company’s enterprise AI strategy staying aligned to the technical side of the house.
Translate strategic priorities into a practical, sequenced AI roadmap with clear owners, milestones, dependencies, and success measures.
Lead the company’s AI Strategy Team, including establishing meeting agendas, facilitating decisions, tracking commitments, and maintaining accountability for results.
Monitor emerging AI capabilities and recommend practical applications that support the company’s business objectives.
Balance speed, value, scalability, compliance, and organizational readiness when prioritizing AI initiatives.
Own the AI tooling budget: forecast spend, evaluate cost against realized value, and recommend consolidation or termination of underperforming tools.
Work directly with Finance, Accounting, Legal, HR, Revenue Operations, Customer Support, Implementations, Customer Success, Sales and other non-technical functions to identify opportunities for AI-enabled automation and improvement.
Evaluate existing processes, challenge established ways of working, and identify opportunities to reduce manual effort, improve quality, accelerate decision-making, and enhance employee and customer experiences.
Facilitate workshops and working sessions to uncover business needs and translate them into actionable AI use cases.
Prioritize opportunities based on expected business value, implementation effort, risk, data availability, and likelihood of adoption.
Develop clear business cases and recommendations for proposed AI initiatives.
Lead AI initiatives from initial concept through solution design, testing, implementation, adoption, and ongoing improvement.
Partner with Business Systems, IT, Compliance, functional leaders, vendors, and other subject-matter experts to develop practical AI-enabled solutions.
Personally drive execution, including documenting requirements, redesigning workflows, coordinating pilots, testing solutions, resolving implementation issues, and managing rollout plans.
Establish repeatable processes and playbooks that allow successful AI solutions to scale across the organization.
Track adoption and solution performance after implementation and make adjustments based on employee feedback and business results.
Develop and execute change-management plans that accelerate AI adoption and help employees successfully transition to new tools and workflows.
Build AI fluency across non-technical teams through training, coaching, demonstrations, office hours, practical use cases, and ongoing communications.
Help employees understand how AI can enhance their work while setting realistic expectations regarding its capabilities and limitations.
Identify and support AI champions within functional teams who can reinforce adoption and share effective practices.
Address resistance to change by understanding employee concerns, engaging leaders, and demonstrating measurable value.
Create reusable educational materials, prompt libraries, implementation guides, and other resources that make AI accessible to employees with varying levels of technical knowledge.
Build alignment among executive leaders, functional teams, Business Systems, IT, and Compliance regarding AI priorities, responsibilities, and expected outcomes.
Coordinate closely with the Compliance team to ensure AI programs are consistent with company policies, regulatory requirements, data privacy obligations, security standards, and responsible AI principles.
Incorporate appropriate controls, documentation, human review, and monitoring into AI-enabled workflows.
Communicate progress, risks, decisions, and results clearly to executive sponsors and other stakeholders.
Ensure teams remain aligned throughout implementation and that issues requiring leadership decisions are escalated promptly.
Establish baseline metrics and success criteria before beginning each AI initiative.
Document and report the tangible and intangible value created by AI programs across each functional team.
Measure outcomes such as time savings, cost reductions, productivity improvements, faster cycle times, increased capacity, improved accuracy, better decision-making, enhanced employee experience, and reduced risk.
Develop dashboards and executive reporting that show implementation progress, adoption levels, realized benefits, and areas requiring additional attention.
Conduct post-implementation reviews to confirm whether anticipated benefits were achieved and identify lessons for future initiatives.
Maintain an enterprise view of the cumulative return on the company’s AI investments.