AI Program Manager

KPFF seeks an organized, pragmatic, and collaborative AI Program Manager to coordinate and mature the firm's AI program. Working closely with the Director of Technology, Shared Services leaders, Risk Management, IT and Security, Data, HR, Marketing, Operations, and Reporting Center leaders, this role helps employees use approved AI capabilities safely, consistently, and effectively.

Because KPFF is a decentralized organization, success in this role will depend on building relationships and influencing across teams rather than relying on formal authority. You’ll work across offices to connect existing efforts, build alignment, and help move shared AI priorities forward.

In this role, you will serve as a practical front door for AI questions, tool requests, use-case ideas, pilot proposals, and enablement needs. You will coordinate governance meetings, maintain program records, support responsible-AI practices, help teams frame and track pilots, deliver training and office hours, and prepare leadership-ready reporting on adoption, risks, decisions, outcomes, and opportunities.

This is a program leadership and change management role focused on helping KPFF put AI into practice across the firm. You do not need to be an AI developer or technical expert. We’re looking for someone who can bring structure to evolving initiatives, connect people and ideas, and help teams adopt new tools and ways of working.

Reporting Relationship

This role reports to the Director of Technology. The AI Program Manager works through established governance and leadership channels and escalates policy, risk, budget, security, legal, vendor, or strategic decisions to the appropriate functional owner or governance body.

What You'll Do

Governance and Program Operations

• Coordinate AI Governance Committee agendas, review materials, decisions, action items, ownership, follow-up, and escalation tracking.

• Maintain the firm-wide AI inventory, use-case register, decision log, exception log, AI-use records, and related program documentation needed for a defensible audit trail.

• Operate the AI intake process as a practical front door for AI questions, tool requests, access requests, proposed use cases, pilots, and enablement needs.

• Track AI program budget inputs, licensing utilization, spend requests, and business-case information for leadership review, while routing approval decisions to the appropriate owner.

AI Portfolio and Roadmap Coordination

• Maintain visibility into AI initiatives, pilots, production solutions, tools, agents, automations, and supporting roadmaps across Reporting Centers and Shared Services.

• Support prioritization discussions by helping evaluate business value, risk posture, feasibility, resource needs, timing, dependencies, and readiness.

• Coordinate status reporting on initiative owners, milestones, dependencies, decisions, risks, lessons learned, and recommended next steps.

• Prepare recommendations for leadership or governance review regarding which initiatives should continue, change, expand, pause, or retire.

Change Management and Communications

• Communicate the why of AI, including benefits, limitations, guardrails, and the role of responsible adoption across the firm.

• Support internal communications such as wins, FAQs, updates, user feedback, lessons learned, and approved-tool reminders.

• Help manage adoption sentiment, address resistance, and support the culture shift required for new ways of working.

• Strengthen the network of relationships and communities needed to sustain AI adoption over time.

Policy, Risk, and Responsible AI Support

• Support implementation and communication of AI policy, the Six Prescriptions, operating guidance, data-handling expectations, and responsible-use practices.

• Help employees understand approved-tool expectations, data classification requirements, human oversight, disclosure expectations, output accountability, and responsible use of AI-assisted work.

• Coordinate reviews for higher-risk use cases, including HR, recruiting, public-facing content, sensitive data, business-system actions, autonomous or semi-autonomous agents, and AI-enabled workflows.

• Monitor relevant AI governance and responsible-use developments and help keep guidance, training, and review materials current in partnership with the appropriate functional owners.

AI Solution Lifecycle and Pilot Coordination

• Help teams frame AI opportunities, define the business problem, document expected outcomes, identify success measures, and prepare use cases for review.

• Coordinate evaluation of proposed tools, prompts, agents, automations, integrations, and AI-enabled workflows with IT, Security, Risk Management, Data, and business stakeholders.

• Track approved pilots, owners, timelines, outcomes, risks, lessons learned, and readiness for broader consideration.

• Support lifecycle practices for review, testing, implementation readiness, monitoring, maintenance, documentation, and retirement of AI-enabled solutions.

Intake, Enablement, Training, and Adoption

• Provide office hours, practical guidance, quick-reference materials, training coordination, and role-based enablement for onboarding and ongoing refresh.

• Build trusted relationships with Reporting Center leaders, AI champions, Shared Services teams, and business stakeholders.

• Promote approved AI tools and responsible-use expectations in a way that encourages voluntary adoption and makes governance feel helpful rather than punitive.

• Capture user feedback, adoption barriers, common questions, and emerging needs, then translate them into improved guidance, communications, and reusable resources.

Tools, Platforms, and Vendor Review Coordination

• Maintain approved-tool and vendor inventory information, platform documentation, review status, and related governance records.

• Coordinate AI tool, vendor, platform, and buy-versus-build reviews using structured criteria for security, compliance, data protection, business value, cost, maintainability, capability, and stakeholder readiness.

• Document evaluation outcomes, open questions, risks, dependencies, and recommendations for review by the appropriate decision makers.

• Track emerging AI tools, market capabilities, and practical opportunities, then summarize relevant findings for governance and leadership review.

Data, Knowledge, Records, Prompts, and Agents

• Partner with IT, Data, and business stakeholders to identify content that may be appropriate for AI-assisted search, reuse, summarization, or knowledge enablement.

• Support consistent storage, discoverability, retention coordination, and ownership tracking for AI-generated artifacts, prompts, agents, decisions, and related records.

• Partner with technical and business teams to help organize and maintain approved AI resources, including prompts, agents, guidance, and related documentation. Identify gaps, duplication, and opportunities to improve reusable AI resources across the firm.

Metrics, Value, and Leadership Reporting

• Maintain program dashboards, adoption summaries, pilot status updates, training activity, utilization indicators, risk themes, and leadership-ready progress reports.

• Track pilot outcomes, productivity indicators, cost impacts, participation, quality improvements, and realized benefits where measurable.

• Identify duplication, common needs, adoption barriers, and opportunities to improve guidance, tools, training, or reusable resources.

• Prepare decision-support materials for leadership regarding AI opportunities, risks, adoption trends, investments, readiness, and recommended next steps. Final decisions remain with the appropriate leadership or governance owner.