Artificial Intelligence

• Support the AI Capabilities & Enablement (AiCE) team in managing and advancing a portfolio of AI, analytics, and digital transformation initiatives that enhance business performance and user experience across field, marketing, and commercial functions.
• Assist with portfolio planning, project tracking, and governance activities across multiple AI and GenAI initiatives.
• Help ensure priorities, milestones, dependencies, risks, and business outcomes are effectively documented and communicated.
• Support the development of executive-ready materials, roadmaps, status updates, and reporting artifacts.
• Coordinate project activities, gather requirements, document business needs, and support launch readiness efforts for emerging AI capabilities.
• Contribute to change management and adoption initiatives by helping develop communications, training materials, and stakeholder engagement plans.
• Assist in analyzing portfolio performance metrics, user feedback, and adoption trends to identify opportunities for optimization, continuous improvement, and future investment.

Fall Co-op – AI Portfolio

• Lead discovery workshops to clarify business objectives, constraints, and measurable success criteria for AI/ML initiatives
• Translate requirements into end-to-end target-state architectures across data, ML/AI, application integration, security, and governance
• Define pragmatic tradeoffs across accuracy, latency, cost, reliability, privacy, and risk—and communicate decisions to exec and engineering audiences
• Design the data + model lifecycle (pipelines, training/finetuning, serving, monitoring, drift detection, retraining) and the required MLOps/LLMOps foundations
• Establish integration patterns with enterprise systems (APIs/events/workflows, IAM, observability) so solutions are operable and supportable in production
• Partner with security, privacy, and risk teams to embed controls (access, auditability, data handling, responsible AI) into solution designs
• Produce core delivery artifacts (architecture diagrams, reference patterns, implementation roadmap, runbooks) and drive architecture reviews
• Mentor teams and build reusable assets/accelerators (reference architectures, templates, evaluation scorecards) to scale repeatable delivery quality

AI-ML Director

• Serve as the operational leader for NCTC’s AI COE, guiding its strategy, governance, day-to-day execution, and continued growth.
• Build and manage the AI COE operating model, including intake, prioritization, milestones, risk management, governance, and lifecycle management of member AI initiatives.
• Develop and manage a portfolio of AI use cases, evaluating opportunities based on member value, technical feasibility, strategic alignment, and return on investment.
• Establish practical AI implementation standards, best practices, reusable tools, and governance frameworks that support responsible and scalable AI adoption across NCTC’s membership.
• Coordinate cross-functional AI delivery teams, including product, data, engineering, vendors, contractors, and member stakeholders, to deliver successful outcomes.
• Define adoption metrics and dashboards that measure member engagement, platform utilization, business impact, and operational performance.
• Partner with Member Success, Product, Sales, and Marketing to increase awareness, adoption, and value realization of AI COE services.
• Evaluate emerging AI technologies, vendors, and strategic partnerships and recommend investments that strengthen the AI COE portfolio.
• Promote responsible AI practices, including appropriate attention to governance, security, privacy, compliance, and ethical use.
• Represent the AI COE in executive discussions, member advisory councils, industry events, and board presentations.
• Lead NCTC’s enterprise business intelligence and data analytics strategy to ensure the organization has trusted, useful, and actionable information to support business decisions.
• Oversee the architecture for NCTC’s core business systems, data pipelines, reporting layers, and analytics capabilities.
• Define and execute a company-wide approach for how data is curated, modeled, governed, and consumed across the organization.
• Establish data quality standards, common metric definitions, and governance practices that support reliable reporting and informed decision-making.
• Enable self-service reporting across NCTC by working with subject matter experts and business leaders to convert available datasets into decision-ready insights.
• Translate business data into reporting and analytics that improve organizational performance and support strategic priorities.
• Develop and maintain NCTC’s enterprise data and AI roadmap, aligning technology priorities with NCTC’s strategic goals, operational needs, and member experience.
• Monitor emerging technologies, automation opportunities, and industry trends to identify practical ways to improve efficiency, enhance services, and support innovation.
• Evaluate and recommend technology investments that support NCTC’s long-term strategy and the evolving needs of its members.
• Encourage a culture of experimentation, knowledge sharing, and continuous improvement across technology and data initiatives.
• Manage relationships with technology vendors, managed service providers, software vendors, cloud providers, and platform partners that support the AI COE and enterprise data initiatives.
• Support the financial and operational performance of the AI COE, including maintaining the AI COE profit and loss statement as approved by the NCTC Board of Directors.
• Optimize software licensing, infrastructure costs, and technology resources to support business priorities and responsible growth.

Executive Director – Artificial Intelligence, Enterprise Data

• Conduct training sessions for SNHU community members to ensure use of AI tools and technologies
• Provide support in the form of hands-on guidance and consultation
• Help optimize existing AI-driven processes to improve operational and educational efficiency
• Collaborate with cross-functional teams to support AI Proofs of Concept, projects, and product exploration
• Assist in brainstorming and planning for faculty and staff ideas related to AI integration
• Develop training materials, guides, and resources to support AI tool adoption across the institution
• Attendance, punctuality, and reliability are essential functions of this role
• Other responsibilities as assigned

AI Integration Specialist

• Lead end-to-end development for our AI platform and customer experiences, from initial roadmap to rollout.
• Partner with engineers to design prompt strategies, evaluation frameworks, and guardrails—balancing latency, cost, and accuracy.
• Serve as the technical translator between engineering and the broader organization, establishing AI best practices and platform standards.
• Drive systematic improvement in answer quality, customer satisfaction, and automation rates through rigorous experimentation.
• Work with partners at OpenAI to evaluate and deploy the next generation of voice models and workflow automation.

Manager, AI Agents and Automation

• Collaborate with the executive leadership team to define the company's CX AI vision, strategy, and goals for contact center transformation
• Drive growth by identifying emerging trends, market opportunities, and industry best practices in contact center innovation
• Lead the planning, development, and execution of the CX AI strategic roadmap, including new innovative offerings in the AI space for contact centers
• Oversee the development and leadership of comprehensive CX AI offerings, including Assistive CX, Agentic CX, Conversation Agents, CX Insights & Intelligence, CCaaS platforms (including Genesys, Five9, AWS Connect, and Google), CRM (Salesforce and Zendesk), workforce management, agent quality management, and technology partnerships (Cresta and ElevenLabs)
• Assume overall accountability for the financial performance of the CX AI practice
• Partner with Business Development, Digital Solutions leaders, and CXM account and operations leaders to grow and transform managed accounts in the BPO business
• In partnership with Business Development, develop and implement effective revenue generation strategies to meet or exceed annual revenue targets for digital contact center solutions
• Monitor financial performance, identify areas for improvement, and implement corrective actions as necessary
• Build and lead high-performing teams across technologies and capabilities
• Foster a culture of excellence, innovation, collaboration, and continuous learning within the CX AI teams globally
• Drive the development and integration of innovative AI-powered solutions and offerings for contact center CX optimization
• Partner with TELUS clients and TELUS Digital stakeholders to drive digital transformation within TELUS-owned CX operations
• Partner with clients to identify their contact center challenges and design tailored digital solutions
• Oversee the delivery of high-quality CX AI implementations and strategic recommendations
• Provide thought leadership and build trusted advisor relationships with key client stakeholders
• Drive the adoption and integration of modern CX platforms and technologies

Managing Director, CX AI Delivery

• Provides strategic support for the assigned business area
• Acts as a day-to-day technical/functional expert in assigned area
• Maintains and supports implementation of policies and procedures
• Implements process improvements
• Analyzes and reports on area data (financial, headcount, etc.) and performance metrics
• Supports business management projects by monitoring and tracking risks, issues and action items
• Drives and oversees meeting planning in support of business projects and objectives
• Influences the development of new strategic initiatives through tracking budgets and milestones

Director – Business Manager, Retirement AI Strategy

• Build and lead market growth strategy for P&C insurers, reinsurers and insurtechs, to include establishing and owning senior prospect relationships.
• Engage C-suite and VP stakeholders (Claims, Data, Underwriting, Risk) as a trusted advisor, not a vendor.
• Operate as a strategic advisor on AI adoption, from use case identification to production deployment and model governance.
• Lead executive discussions on how AI, particularly human-in-the-loop approaches, can improve efficiency, accuracy, and regulatory defensibility.
• Align complex stakeholder groups across claims, actuarial, IT, data science, and compliance functions.
• Identify and drive expansion opportunities within existing accounts.
• Own new logo acquisition, account expansion and P/L management across enterprise P&C clients in the US and Europe.
• Develop strategic account plans that scale from initial use cases to enterprise-wide AI programs.
• Own the full commercial lifecycle: discovery, solution framing, proposal development, and executive presentations.
• Navigate procurement processes, RFPs, vendor risk frameworks, and regulatory constraints effectively.
• Partner with internal teams to craft tailored, high-impact solutions for insurance clients.
• Identify high-impact AI use cases across the insurance value chain, including:
• - Claims document processing and intelligent document understanding
• - Aerial and satellite imagery analysis for property assessment
• - NLP for policy, coverage, and regulatory interpretation
• - Underwriting data enrichment and risk model validation
• - FNOL automation and subrogation workflows
• Lead discovery sessions and workshops to uncover transformation opportunities.
• Translate operational and regulatory challenges into scalable AI solutions.
• Collaborate closely with data science and engineering teams to ensure successful execution.
• Maintain accountability for delivery quality, timelines, and client satisfaction.
• Stay at the forefront of AI trends in insurance, including fraud detection, intelligent document processing, and risk modeling.
• Represent CloudFactory in industry forums, client workshops, and executive discussions.
• Demonstrate strong awareness of regulatory frameworks (e.g., NAIC guidelines, EU AI Act, model risk management standards).
• Feed market insights back into product development and go-to-market strategy.
• Lead and influence cross-functional teams across consulting, data science, and delivery.
• Foster a culture of collaboration, innovation, and continuous improvement.
• Contribute to knowledge sharing and best practices across engagements.

Client Principal, AI Consulting – Property & Casualty Insurance

• Engage with executive stakeholders and internal teams to align AI initiatives with measurable business objectives.
• Lead strategic advisory engagements focused on AI adoption, value realization, customer experience transformation, operational improvement, and outcome definition.
• Facilitate executive workshops, AI strategy sessions, value realization discussions, and outcome-focused planning activities.
• Translate customer business goals, operational constraints, and experience challenges into practical AI opportunity roadmaps.
• Help customers and internal teams prioritize AI use cases based on value potential, feasibility, readiness, data availability, and measurable impact.
• Develop clear narratives that connect AI capabilities to business outcomes, operational performance, customer experience improvement, and long-term value realization.
• Develop KPI frameworks, value realization models, measurement strategies, benchmarking approaches, and business impact models.
• Analyze customer operational, journey, interaction, digital, routing, bot, and experience data to identify friction, constraints, and improvement opportunities.
• Establish baseline measurement approaches that help customers understand current-state performance before AI initiatives are scaled or optimized.
• Create executive-ready reporting, scorecards, business cases, and analytical summaries that quantify AI impact and identify opportunities for improvement.
• Apply statistical, analytical, and modeling techniques to evaluate trends, performance drivers, adoption gaps, and optimization opportunities.
• Support before-and-after measurement strategies that help determine whether AI initiatives are producing meaningful business change.
• Evaluate customer readiness for AI adoption, including operational maturity, data availability, reporting capability, KPI clarity, governance, and organizational readiness.
• Develop phased AI transformation strategies that help customers move from experimentation to measurable impact.
• Identify opportunities to improve customer experience, operational efficiency, self-service effectiveness, routing performance, agent productivity, and adoption of AI-enabled capabilities.
• Help customers validate whether existing AI investments are producing expected value and identify where tuning, redesign, enablement, or operating model changes may be needed.
• Provide thought leadership on outcome-led AI, value realization, AI readiness, customer experience optimization, and measurable transformation.
• Contribute to the continued development of the AI Outcomes methodology, including outcome intelligence, applied AI, and outcome engineering frameworks.
• Create repeatable tools, accelerators, playbooks, KPI libraries, value models, assessment methods, and analytical templates that improve consistency and scalability.
• Develop practical guidance that helps internal teams frame customer conversations around measurable outcomes rather than standalone capabilities.
• Mentor consultants, strategists, delivery leaders, and customer-facing teams on outcome-driven AI strategy, KPI mapping, and value realization approaches.
• Partner with Professional Services, Customer Experience Advisory, Technical Account Managers, Customer Success leaders, and other internal teams to support complex customer scenarios.

Principal, AI Strategy, Analytics

• Define and drive the strategic direction and operational execution of Artificial Intelligence capabilities
• Own the development, communication, and execution of the enGen AI roadmap
• Drive AI adoption and programs within enGen and across the enterprise
• Commercialize enGen's AI capabilities to identify and seed new revenue streams
• Create and nurture strong partnerships across the enterprise and within enGen
• Deliver flexible, high-quality AI solutions and operational frameworks adhering to privacy policies

VP AI Strategy – Enablement

• Support the enterprise Authorized Provisioning Point / Authorized Data Source program within the AI & Data Organization
• Support the definition of a data domain based model, partner with stakeholders across architecture, technology delivery, and the LOB to define strategies and implementation roadmaps to bring the program into reality
• Support program execution and asset certification
• Draft and maintain corresponding policies, frameworks, standards, and procedures
• Support data-products strategy and intersection with enterprise ontologies
• Support the definition and implementation of an operating model to cover data asset ownership and data stewardship
• Support the implementation of core data management and governance capabilities against identified data assets
• Develop and maintain policies, standards and technology in support of enterprise Data Governance
• Create and implement processes and procedures to support data standards and control frameworks
• Provide subject matter expertise in the planning and execution of data management activities such as data sourcing, metadata management, data quality, data privacy or records management
• Drive solution design and execution of multi-pronged data governance efforts that span across platforms and business/technology areas to address enterprise data needs
• Implement strategic data governance capabilities by working with business and technology partners to document requirements and create action plans
• Perform oversight and inspection of critical data management practices for adherence to established data policies and control frameworks
• Identify data issues and work with technology, risk and business partners to triage, track, communicate, mitigate and remediate the issues to closure
• Support the production of metrics and measures to track progress and adherence, escalating as needed to various committees for visibility and program accountability
• Understand and integrate relevant regulations and industry trends into work plans, exploring emerging frameworks and assessing feasibility using proof of concepts
• Collaborate closely with peer teams to ensure coordination, synergy and seamless overall execution
• Champion and drive improvement in enterprise data management practices throughout the organization

AI & Data Consultant – Data Governance, Authorized Provisioning Point

• Manage a portfolio of member relationships providing Advisory support to the C-Suite with a focus on Artificial Intelligence
• Leverage subject matter expertise to create service solutions for clients utilizing all ExP and/or EITL products
• Define and deliver innovative solutions by assessing member Mission Critical Priorities (MCPs)
• Conduct a mix of on-site and virtual briefings, including strategy sessions and webinars
• Build a strong partnership with Gartner’s Sales organization and collaborate with them for member engagement
• Guide executives who lead strategic initiatives using AI and provide expert advice on implementation and optimization
• Provide training and mentorship on AI-related topics to broad audiences across organizations

Executive Partner, Artificial Intelligence Advisory – AI Strategist

• Serve as EnerSys’ executive leader and single point of accountability for enterprise AI strategy, execution, and outcomes.
• Translate enterprise and business strategies into a clear, multi‑year AI vision and roadmap.
• Advise the CIO, ELT, and Board on AI trends, risks, opportunities, and competitive implications.
• Represent EnerSys externally with strategic AI partners, technology providers, and industry forums.
• Design and implement the enterprise AI operating model, including governance forums and funding processes.
• Establish enterprise standards for responsible AI, data usage, security, privacy, and risk management.
• Own AI investment governance, ensuring alignment with capital planning and transformation funding.
• Own the global AI use case portfolio and prioritization framework.
• Define, track, and report enterprise AI value metrics.
• Orchestrate cross-functional delivery across IT, data, and business units.
• Partner with HR to lead enterprise-wide change management and AI literacy initiatives.
• Build, lead, and develop a high performing enterprise AI organization with clear roles.

VP, Enterprise AI Enablement

• Be the one building AI-powered experiences where they matter most.
• Help build, support and operate technology used by more than 8,000 organizations in over 100 countries.
• Develop NLU models and perform prompt engineering strategies.
• Work directly with customers to understand requirements and explain improvements.
• Design and develop prompts for Agentic Virtual Agents to drive task completion.
• Analyze failures in LLM-driven interactions and identify root causes.
• Create and curate high-quality training data to maximize coverage and accuracy.
• Measure and track NLU performance using defined evaluation metrics and test sets.

Agentic AI, NLU Engineer – English, Spanish

• Lead the enterprise AI activation and transformation function, including building and guiding a team responsible for AI strategy, enablement, and execution.
• Establish a long-term vision that balances innovation with responsible adoption.
• Translate enterprise priorities into a clear, actionable AI strategy.
• Identify opportunities to re-engineer business processes using AI, from problem identification through implementation and value realization.
• Balance near-term productivity gains with longer-term innovation efforts across a diversified AI portfolio.
• Lead BECU’s internal AI innovation incubator that operates as an internal VC fund, identifying internal opportunities to drive change, funding them, and tracking them as part of the broader AI portfolio.
• Oversee AI governance, including policies, standards and decision frameworks that enable responsible and scalable adoption.
• Partner with leaders across business, technology, and operations to embed AI into real workflows.
• Establish and evolve enterprise AI governance, including policies, standards, and decision frameworks that ensure ethical, compliant, and scalable AI adoption.
• Build organizational capability through education, coaching, and enablement—helping employees develop confidence and fluency in AI tools.
• Influence senior leaders and manage cross-functional partnerships, ensuring alignment with regulatory expectations, risk tolerance, and member trust.

VP, AI Transformation

• Lead the development and execution of the Tech+Talent 2026 marketing strategy to achieve key business objectives.
• Utilize market research to identify trends, customer needs, and insights that shape and inform our marketing tactics.
• Design and implement innovative marketing campaigns tailored to targeted customer segments, ensuring alignment with strategic goals.
• Develop clear and compelling solution positioning and messaging that differentiates Axiom's offerings with a specific focus on Axiom’s AI capabilities.
• Collaborate with strategy, technology, and commercial teams to convert capabilities into customer-centric benefits and articulate these in marketing collateral.
• Create engaging sales enablement materials, including solution briefs, presentations, and case studies to support sales efforts.
• Drive the execution of our marketing plan for new solution launches, ensuring seamless integration across multiple digital channels.
• Coordinate with marketing communications to deploy campaigns that drive brand awareness and increase demand generation.
• Analyze marketing campaign performance and leverage data-driven insights to refine and optimize strategies continuously.
• Work closely with sales teams to capture customer insights and refine solution selling approaches.
• Engage with strategy teams to deliver market feedback that guides prioritization of initiatives.
• Collaborate with commercial teams to harness customer experiences in marketing narratives and success stories.
• Maintain detailed project plans, timelines, and documentation for marketing initiatives.
• Identify and mitigate potential risks to ensure successful program delivery.

Senior Manager, AI Solution Marketing

• Facilitate co-design of the AI-enabled HR operating model across the employee lifecycle in partnership with HR functions, leaders, and subject matter experts.
• Lead structured design sessions to align on future-state workflows, service delivery models, decision rights, and role implications.
• Ensure operating model designs balance operational effectiveness, scalability, and a cohesive, human-centered employee experience.
• Translate enterprise strategy into practical workflow blueprints with clear governance and ownership structures.
• Design integrated employee journeys that connect processes, platforms, and touchpoints into a seamless lifecycle experience.
• Align AI-enabled workflows to reinforce and operationalize the company’s Employee Value Proposition, ensuring consistency across interactions.
• Reduce friction, handoff breakdowns, and system silos that create fragmented employee experiences.
• Define experience-focused KPIs, including effort score, perceived responsiveness, trust, adoption, and sentiment, alongside operational performance metrics.
• Partner with HR subject matter experts, HRIS, IT, and shared services teams to co-design end-to-end workflows integrating Workday, ServiceNow, Genesys Cloud, and related technologies.
• Define orchestration logic, automation triggers, AI intervention points, and escalation pathways.
• Ensure workflow designs are intuitive, transparent, compliant, and scalable across a global workforce.
• Align integration decisions with enterprise architecture standards and long-term technology strategy.
• Advise HR leaders on where AI augments human expertise, including personalization, insight generation, and decision support, and where automation reduces repetitive, low-value work.
• Evaluate use cases through both business impact and employee experience lenses.
• Apply structured frameworks to assess value, feasibility, readiness, and risk prior to scaling solutions.
• Embed responsible AI principles into workflow design and governance models.
• Develop impact models that quantify operational gains, including cycle time reduction, cost-to-serve improvement, and productivity shifts.
• Measure experience improvements aligned with EVP commitments and organizational culture.
• Present structured design options with clear trade-offs to enable informed, data-driven decision making.
• Ensure workflow redesign delivers measurable business outcomes and sustainable value realization.
• Act as a strategic design partner across HR Centers of Excellence, shared services, and business-facing teams to ensure alignment and coherence.
• Build strong partnerships with IT and HRIS to bridge business intent and technical feasibility.
• Establish guiding design principles that reinforce simplicity, integration, compliance, and EVP alignment.
• Surface system dependencies, sequencing risks, and organizational impacts early to support responsible implementation planning.

Principal – Operational Excellence, AI Enablement

• Drive product strategy and execution across a portfolio of no-code and low-code AI products and workflow automation capabilities, with a focus on improving operational efficiency, strengthening controls, and delivering measurable business value.
• Partner with product leadership to define strategic priorities, clarify objectives, and translate business goals into actionable roadmaps, operating plans, and execution routines.
• Identify opportunities to create business value by assessing operational challenges, process inefficiencies, stakeholder needs, and potential technology-enabled solutions.
• Connect work across teams, products, and business groups to identify synergies, reduce duplication, and improve alignment across the product portfolio.
• Support innovation efforts by helping evaluate new ideas, structure exploratory work, define success criteria, and ensure experimentation is connected to measurable business outcomes.
• Establish and manage operating routines, including leadership cadence, portfolio reviews, intake forums, prioritization discussions, status updates, and executive-ready communications.
• Develop frameworks, materials, and reporting that help leadership make informed decisions on strategic priorities, resources, risks, dependencies, delivery progress, adoption outcomes, and business value.
• Partner with product pods to anticipate and remove execution roadblocks, manage dependencies, and support alignment across business, product, technology, risk, and control stakeholders.
• Support resource planning, demand management, intake prioritization, and portfolio-level visibility to help ensure the team is focused on the highest-value initiatives.
• Prepare clear, concise, and well-structured communications for leadership and stakeholder audiences, including strategic updates, decision materials, meeting summaries, adoption materials, and portfolio narratives.
• Use data, metrics, stakeholder feedback, and business outcomes to assess progress, identify improvement opportunities, and support continuous improvement across the product organization.
• Promote a culture of collaboration, accountability, operational excellence, risk awareness, adoption discipline, and continuous learning.

Lead Strategy & Planning Consultant – AI Product Strategy, Innovation

• Own and drive TIAA’s enterprise-wide AI strategy, vision and multi-year roadmap
• Serve as a trusted strategic partner to senior business leaders across the enterprise
• Evangelizes use of AI services and other emerging technology within the company
• Lead on TIAA’s thinking on its AI products and services
• Expand product roadmaps for current tooling and envision new products and services for the enterprise
• Liaise with the broader enterprise and affiliates to ensure that innovation outcomes are efficiently leveraged
• Lead thought leadership, research and intellectual property initiatives in the technology and AI space
• Establish agile innovation processes which allow the company to easily adjust current technologies to changes in the market

Senior Managing Director – AI Strategy, Enterprise Applications

• Develop and own the AI adoption roadmap across RTI Main, translating strategy into prioritized initiatives and measurable outcomes
• Identify and prioritize high-value AI use cases that drive revenue, efficiency, or client impact
• Lead a portfolio of signature AI initiatives, executed as structured sprints with clear baselines, targets, and accountable owners
• Ensure all initiatives align with ODAS governance, responsible AI guardrails, and Client Technology capabilities
• Operate within ODAS enterprise standards, the approved tool catalog, and responsible AI guidelines—these are the rules of the road, not suggestions
• Populate and maintain Client AI Compliance Registry entries for RTI Main’s portfolio—surfacing contract-specific AI restrictions, disclosure requirements, and data classification constraints upward to ODAS
• Represent RTI Main on the AI Council, bringing field intelligence that ODAS alone cannot generate
• Establish and lead a network of AI Leads embedded within RTI Main functions, each reporting to their functional leader with a matrix line to this role
• Define decision rights, operating cadence, and accountability mechanisms across the network
• Develop practical playbooks, templates, and reusable patterns that enable scaling AI across repeatable workflows and specialized use cases
• Own the application of ODAS’s classification standard within RTI Main—determining which workflows go AI-first (speed and cost advantage) and which remain human-critical (trust, scientific rigor, client relationship value)
• Ensure functions are not pressured to automate what clients and the scientific mission value as human effort and judgment
• Translate AI capabilities into tangible business outcomes: revenue growth, cost reduction, cycle time improvements, and enhanced client experience
• Partner with Growth and Marketing to embed AI into pipeline development, proposal processes, and competitive positioning
• Partner with Solutions to integrate AI into research and delivery workflows while maintaining scientific rigor
• Package and communicate results as replicable proof points, including playbooks, case studies, and board-ready materials
• Drive adoption through structured change management, communication, training, and stakeholder engagement
• Build and lead the AI Lead network, including recruitment, development, and performance management of matrixed contributors
• Foster a culture of experimentation, accountability, and responsible AI use across RTI Main
• Ensure teams have the time, funding, and support required to execute AI adoption priorities
• Define and manage an AI adoption performance framework with KPIs tied to business outcomes (revenue impact, cost savings, cycle time improvements, decision redistribution)
• Develop dashboards and reporting mechanisms to track adoption progress and inform prioritization
• Coordinate with ODAS on measurement alignment so governance and adoption narratives are consistent for Executive Committee and Board audiences
• Continuously refine adoption strategy based on performance data, emerging AI capabilities, and evolving business priorities

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