The Manager, Security, AI & Data Programs is responsible for organizational effectiveness, integrated portfolio visibility, executive communications, performance reporting, operational planning, and cross-functional coordination across Flexential's Security, AI, and Data organizations. Reporting directly to the executive leading these functions, this role acts as a trusted right hand and force multiplier by turning priorities into structured plans, maintaining a reliable view of commitments and results, and ensuring decisions and follow-through move across all three pillars.
The role serves as the operational owner of the enterprise AI portfolio, guiding intake, prioritization, business case development, process redesign, build-versus-buy analysis, pilot management, production transition, adoption, and value realization. It connects business sponsors with AI Engineering, Security, Data, Enterprise Architecture, Legal, Privacy, Compliance, Procurement, Finance, and vendors so approved initiatives advance through a consistent lifecycle with clear ownership and measurable outcomes. This role does not own Security engineering, AI engineering, enterprise data strategy, data governance execution, architecture, or technical delivery. It provides the connective tissue across those disciplines through disciplined operating practices, portfolio management, governance coordination, executive communications, adoption planning, value tracking, and stakeholder engagement.
Responsibilities Organizational Operations & Executive Partnership
- Run the operating cadence for the Security, AI, and Data organization, including leadership staff meetings, planning sessions, QBRs, steering committees, roadmap reviews, and action follow-up.
- Prepare executive briefings, decision materials, board content, talking points, investment requests, and concise updates for executive leadership and governance forums.
- Anticipate information, decisions, reporting, and coordination needed by functional leaders and the executive sponsor, and drive work to closure without waiting for detailed direction.
- Act as the executive's operational delegate in selected meetings, accurately representing priorities, commitments, and decisions while escalating matters requiring executive judgment.
- Maintain an integrated calendar of strategic initiatives, governance forums, reporting cycles, funding decisions, portfolio reviews, and organizational dependencies.
- Develop operating models, intake workflows, governance processes, and reporting mechanisms that create transparency and accountability across Security, AI, and Data.
Integrated Portfolio Visibility & Prioritization
- Create and maintain a centralized, decision-ready view of priorities, initiatives, milestones, accountable owners, dependencies, risks, resource requirements, and leadership decisions across Security, AI, and Data.
- Partner with functional leaders to translate roadmaps into an integrated portfolio view without assuming ownership of their domain strategies or technical delivery.
- Facilitate prioritization and sequencing based on business value, risk reduction, EBITDA contribution, strategic alignment, readiness, capacity, dependencies, and available funding.
- Identify cross-pillar conflicts, duplicated effort, stalled decisions, capacity constraints, and execution risks early; coordinate resolution or escalate with clear options and tradeoffs.
- Establish lightweight, repeatable methods for intake, prioritization, status reporting, escalation, decision records, and closure.
AI Portfolio & Program Leadership
- Own operational management of the enterprise AI portfolio from intake through value realization, ensuring initiatives align with enterprise strategy, business priorities, risk tolerance, and measurable outcomes.
- Lead AI use-case intake, qualification, prioritization, sequencing, and business case development.
- Evaluate opportunities using business value, EBITDA contribution, revenue enablement, cost avoidance, risk reduction, adoption potential, feasibility, data readiness, investment requirements, and enterprise reusability.
- Facilitate process discovery and redesign before automation begins so AI is applied to optimized workflows rather than existing inefficiencies.
- Coordinate build-versus-buy evaluations, vendor assessments, platform analysis, commercial considerations, and executive recommendations.
- Coordinate initiatives through concept definition, pilot execution, production readiness, deployment, adoption, operational transition, ownership assignment, and sustained support.
- Maintain an enterprise inventory of AI use cases, pilots, agents, automations, production deployments, business sponsors, data dependencies, risks, investments, and realized value.
- Identify duplicate, overlapping, redundant, or low-value initiatives and recommend consolidation, reuse, redirection, hold, or cancellation.
- Establish success measures, adoption targets, pilot exit criteria, production readiness requirements, value targets, and business ownership expectations.
- Serve as the primary coordination point among business sponsors, AI Engineering, Security, Data, Enterprise Architecture, Legal, Privacy, Compliance, Procurement, Finance, and vendors.
- Lead AI steering committee administration, governance forums, decision tracking, action management, and executive reporting.
- Coordinate AI literacy programs, communities of practice, adoption campaigns, communications, and stakeholder engagement.
- Ensure initiatives progress through consistent governance, risk, privacy, security, architecture, deployment, adoption, and measurement practices.
AI Value Realization & Portfolio Performance
- Establish and maintain enterprise AI portfolio dashboards and scorecards covering strategic alignment, investment, progress, adoption, risk, and realized outcomes.
- Define value measurement plans with business sponsors before pilots begin and confirm accountable ownership for baseline data and benefit validation.
- Measure actual versus planned benefits, including cost avoidance, operational efficiency, revenue enablement, risk reduction, productivity improvement, customer impact, and adoption.
- Coordinate post-implementation reviews and lessons learned to assess whether initiatives should scale, continue, change direction, pause, or stop.
- Maintain executive reporting on portfolio performance, investment consumption, adoption trends, risks, and value realization.
- Use measured outcomes to inform annual planning, quarterly portfolio decisions, funding recommendations, and future use-case prioritization.
Metrics, Reporting & QBR Leadership
- Lead preparation and facilitation of Security, AI, and Data QBRs, ensuring each review focuses on outcomes, risks, decisions, investment needs, and next-quarter priorities.
- Consolidate functional metrics into executive scorecards and narratives that provide a clear view of organizational performance and business value.
- Partner with domain leaders to define reporting expectations and ensure measures are supported by accountable owners and reliable source data.
- Translate technical and operational detail into concise implications, options, and decisions for executive audiences.
- Maintain a single source of truth for executive reporting and ensure recurring reports remain consistent, current, and action-oriented.
Cross-Functional Partnership & Organizational Reputation
- Build durable relationships across IT, Product, Architecture, Operations, Finance, People & Culture, Legal, Risk & Compliance, Privacy, Procurement, Sales, Marketing, and other business functions.
- Serve as a responsive coordination point for work crossing Security, AI, and Data boundaries, directing issues to the appropriate functional owner and maintaining follow-through.
- Improve stakeholder experience through early engagement, transparency, practical communication, and solution-oriented collaboration.
- Develop communication and change plans for major initiatives, AI adoption, governance activities, and organizational changes.
- Capture stakeholder feedback, identify recurring friction, and recommend improvements to engagement models, processes, and communications.
Planning, Budget & Resource Coordination
- Coordinate annual and quarterly planning inputs across Security, AI, and Data, including priorities, outcomes, dependencies, capacity assumptions, and resource needs.
- Maintain visibility into approved investments, capital requests, hiring plans, vendor commitments, contract renewals, resource allocations, and material budget risks in partnership with functional owners and Finance.
- Support business cases and investment requests by organizing the problem statement, expected outcomes, costs, risks, dependencies, adoption approach, and measures of value.
- Track leadership commitments and decisions affecting scope, timing, funding, staffing, or expected benefits and reflect those changes in portfolio reporting.
Role Boundaries
- The Director of Information Security owns Security strategy, technical roadmap, architecture, engineering, and security operations.
- The Director of Enterprise Data owns enterprise data strategy, architecture, integration, platforms, governance, analytics enablement, and Data team delivery.
- AI Engineering owns technical design, development, testing, deployment, and operation of AI solutions and platforms.
- Enterprise Architecture owns technology standards, architectural governance, and platform design decisions.
- This role owns integrated visibility, operating cadence, AI portfolio operations, program coordination, executive reporting, value realization management, adoption coordination, communications, and follow-through.
- This role coordinates governance activities and decision forums but does not replace accountable governance, risk, legal, privacy, compliance, architecture, or technical owners.
What Success Looks LikeFirst 6 Months
- Establish a consistent leadership cadence with clear agendas, decisions, owners, due dates, and follow-through.
- Create a trusted, centralized portfolio view across Security, AI, and Data that leaders use to prioritize work and surface decisions.
- Lead an effective QBR process with concise, outcome-focused materials and clear next-quarter commitments.
- Standardize executive reporting and reduce manual consolidation required from the executive and functional leaders.
- Establish enterprise AI intake, prioritization, governance, pilot management, production transition, adoption, and value realization practices.
- Launch an AI portfolio dashboard tracking investments, priorities, ownership, risks, adoption, and outcomes.
- Build productive working relationships across partner organizations and improve the clarity and responsiveness of cross-functional engagement.
12-Month Outcomes
- Security, AI, and Data operate with shared visibility into priorities, investments, dependencies, risks, decisions, and measurable outcomes.
- Functional leaders spend less time assembling status information and more time leading teams and delivering domain outcomes.
- Executive and board-level materials are accurate, concise, consistent, and supported by repeatable reporting practices.
- AI investments move through standardized intake, prioritization, pilot, production, adoption, and value realization stages with clear ownership and measurable outcomes.
- Duplicate, stalled, or low-value AI efforts are identified earlier and redirected, consolidated, held, or stopped.
- Business partners experience the organization as coordinated, transparent, responsive, and focused on practical business outcomes.
- Measured value and adoption results inform future investment and portfolio decisions.
Required Qualifications - 5+ years of progressive experience in technology program management, business operations, organizational effectiveness, portfolio management, or a related role within a complex enterprise environment.
- Demonstrated success leading cross-functional programs involving technical teams, business stakeholders, executives, and external partners.
- Experience with executive communications, board materials, dashboards, scorecards, reporting, and governance forums.
- Experience building operating cadences, portfolio visibility, prioritization frameworks, risk and dependency tracking, and decision-management practices.
- Experience supporting AI programs, digital transformation, enterprise technology portfolios, innovation initiatives, or comparable business change.
- Understanding of AI adoption, governance, change management, business process redesign, build-versus-buy analysis, and value realization concepts.
- Ability to evaluate business value, frame strategic tradeoffs, facilitate decisions, and work through influence without formal authority.
- Exceptional written, verbal, visual, facilitation, relationship-building, and follow-through skills.
- Ability to maintain confidentiality and operate effectively with ambiguity, competing priorities, and limited oversight.
Preferred Qualifications - Experience supporting a CISO, CIO, Chief Data Officer, AI leader, or executive responsible for multiple technology functions.
- Experience with AI use-case intake, business cases, pilots, governance, adoption, portfolio reporting, and value realization.
- Familiarity with Security, Data, Analytics, Enterprise Architecture, Software Delivery, Cloud Platforms, and AI technologies.
- Experience with Microsoft 365, PowerPoint, Excel, Power BI, SharePoint, Teams, ServiceNow, Azure DevOps, Planner, or comparable work-management platforms.
- PMP, CSM, Prosci/CCMP, Lean Six Sigma, AIGP, or comparable program, agile, change-management, or AI governance certification.
Ideal Candidate Profile - A trusted operator who combines sound judgment, discretion, initiative, and strong follow-through.
- A strategic systems thinker who sees relationships among priorities, people, risks, data, investments, decisions, and business outcomes.
- An excellent communicator who can move comfortably between
