Engineering a world of possibilities
Join Mines in a new AI Solutions Manager position!
The AI Solutions Manager is a member of the AI Acceleration team within the Information Technology department at Mines and serves as the primary customer-facing intake, engagement, adoption, and value-realization lead for agentic AI opportunities. This role manages the AI solution lifecycle from idea intake through use-case development, prioritization, implementation readiness, adoption planning, change management, feedback collection, and outcome measurement.
Working closely with IT teams, and campus partners, the AI Solutions Manager helps departments identify meaningful opportunities to use agentic AI to improve academic, administrative, research, and operational outcomes. This role translates campus needs into clear AI use cases, assesses value and readiness, coordinates stakeholder alignment, and helps ensure that AI work is prioritized, adopted, and measured in a responsible and sustainable way.
This is a high-visibility individual contributor role that requires strong relationship-building, analytical judgment, change management experience, business acumen, and the ability to communicate clearly with technical and non-technical audiences. The AI Solutions Manager does not manage people; the role manages the AI opportunity pipeline, campus engagement process, adoption lifecycle, and value-realization activities for AI-enabled solutions.
This position currently operates in a hybrid work model with regular campus presence required. Work arrangements are subject to change based on institutional needs. The successful candidate must be able to commute to campus in Golden, Colorado.
Visa sponsorship is not available for this position now nor in the future.
Primary Responsibilities
AI OPPORTUNITY INTAKE, PIPELINE MANAGEMENT, AND PRIORITIZATION SUPPORT
- Serve as the primary front door for campus AI opportunities, ideas, use cases, and requests from academic, administrative, research, and operational units.
- Build and maintain an organized AI opportunity pipeline that captures request details, business needs, expected outcomes, stakeholders, readiness factors, dependencies, risks, and status.
- Meet with campus partners to understand pain points, opportunities, goals, current processes, service impacts, customer needs, and potential value of AI-enabled solutions.
- Shape early ideas into clear, actionable use cases that can be evaluated by the AI Acceleration team and institutional decision-makers.
- Assess incoming opportunities for institutional alignment, business value, feasibility, urgency, complexity, risk, readiness, data needs, governance considerations, accessibility, privacy, security, and sustainability.
- Develop prioritization recommendations for review by the Director of AI Acceleration and appropriate governance or leadership groups.
- Identify requests that should move forward as AI projects, requests that need additional discovery, requests that are better addressed through training or process improvement, and requests that should be deferred or declined.
- Partner with the Senior Project Manager to transition approved AI opportunities into structured project planning and delivery processes.
- Track the AI opportunity pipeline and prepare summaries, dashboards, presentations, or decision-support materials for leadership, governance groups, and stakeholders.
- Evaluate potential solution approaches, including AI-enabled solutions, enterprise applications, workflow automation, process improvements, vendor products, and existing technology capabilities, to help identify practical and sustainable paths forward.
CAMPUS ENGAGEMENT, PARTNERSHIP, AND AI CONSULTING
- Establish and maintain trusted relationships with campus departments, faculty, staff, administrative leaders, researchers, IT teams, and other stakeholders interested in AI-enabled solutions.
- Serve as a consultative partner to departments by helping them understand how AI may support business process improvement, service delivery, operational efficiency, productivity, decision support, and customer experience.
- Facilitate discovery conversations, stakeholder workshops, interviews, listening sessions, demonstrations, and other engagement activities to understand needs and align expectations.
- Translate campus needs and user perspectives into clear narratives, business cases, use-case summaries, stakeholder impacts, adoption considerations, and success measures.
- Help departments understand responsible AI expectations, approved tools, data handling considerations, governance requirements, and appropriate use boundaries.
- Partner with AI Solutions Architects to ensure campus needs are clearly understood before technical design, prototyping, or implementation begins.
- Support communication between technical teams and campus partners so that AI concepts, solution options, tradeoffs, constraints, and decisions are understandable to non-technical audiences.
- Identify opportunities to expand AI fluency and responsible AI adoption across campus through targeted outreach, documentation, office hours, presentations, and engagement activities.
- Connect related requests, common pain points, and recurring needs across departments to identify scalable AI solutions and reduce one-off delivery patterns.
- Advise stakeholders on available technology options and approaches by evaluating tradeoffs, capabilities, limitations, implementation considerations, support requirements, and organizational impacts.
ADOPTION, ORGANIZATIONAL CHANGE MANAGEMENT, AND READINESS
- Lead adoption planning for AI-enabled solutions, including stakeholder readiness, communication needs, training needs, workflow impacts, support model considerations, and resistance management.
- Develop change management approaches that help faculty, staff, and departments understand, accept, and effectively use AI solutions in their work.
- Partner with project teams, communications staff, training resources, service owners, and campus departments to coordinate implementation readiness and adoption support.
- Create or coordinate communication plans, stakeholder impact summaries, adoption plans, training materials, knowledge articles, FAQs, user guidance, and other enablement resources.
- Assess department readiness for AI-enabled change, including process maturity, stakeholder support, data availability, operational capacity, governance needs, and likely adoption barriers.
- Monitor adoption after implementation and identify whether additional communication, training, documentation, process adjustment, or technical refinement is needed.
- Gather user feedback and work with AI Solutions Architects and project teams to support solution iteration, improvement, and sustained use.
- Promote practical, ethical, secure, accessible, and responsible AI adoption consistent with Mines policy, data governance expectations, and institutional priorities.
- Help build a culture of AI fluency by reinforcing effective use, responsible experimentation, practical examples, and shared learning across campus.
VALUE REALIZATION, METRICS, AND CONTINUOUS IMPROVEMENT
- Define expected outcomes and success measures for AI opportunities in partnership with campus stakeholders, the Director of AI Acceleration, AI Solutions Architects, and project teams.
- Develop and track value-realization measures such as adoption, user satisfaction, effort reduction, process improvement, service quality, cycle-time reduction, accuracy, risk reduction, cost avoidance, or other relevant outcomes.
- Collect feedback from users and stakeholders after implementation to evaluate whether AI solutions achieved the intended business or operational value.
- Prepare summaries, reports, dashboards, presentations, and recommendations that communicate AI outcomes, lessons learned, realized value, adoption challenges, and future opportunities.
- Identify patterns across AI requests and delivered solutions to recommend improvements to intake processes, prioritization criteria, governance workflows, adoption practices, and service delivery.
- Partner with the Senior Project Manager to support post-implementation reviews, lessons learned, project closure, and transition to operational support.
- Maintain documentation of use cases, decisions, outcomes, lessons learned, success stories, and reusable practices to support future AI work.
- Recommend improvements to the AI opportunity intake model, prioritization methods, change management practices, campus engagement approach, and value tracking framework.
AI GOVERNANCE, RESPONSIBLE USE, AND CROSS-FUNCTIONAL ALIGNMENT
- Support responsible AI implementation by helping ensure proposed use cases consider privacy, security, accessibility, data governance, compliance, model transparency, user impact, and institutional risk.
- Identify AI use cases that may require review by governance, compliance, security, legal, accessibility, data governance, or other institutional stakeholders.
- Partner with the Director of AI Acceleration, AI Solutions Architects, Information Security, Compliance, Procurement, Academic Affairs, and other relevant teams to support responsible and aligned AI decision-making.
- Help translate governance expectations into practical guidance for departments and project teams.
- Ensure AI intake, prioritization, adoption, and value-realization activities align with institutional goals, IT standards, and Mines’ responsible AI expectations.
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