Vice President Research, AI Planning and Operations

Overview

This role supports the organization’s AI Economics research efforts, helping enterprise leaders prioritize investments in artificial intelligence (AI), understand the full cost of deployment and operation, and measure business value across a portfolio of business processes and use cases.

The position is designed for a senior practitioner who has held direct responsibility for the financial and operational outcomes of AI deployments in large organizations across multiple business functions and domains. You will translate that experience into independent research, financial models, and executive guidance for chief information officers (CIOs), chief financial officers (CFOs), and business leaders.

Responsibilities

• Contribute to the enterprise AI economics research agenda, using deployment experience to address investment prioritization, budgeting, forecasting, cost management, and value realization across business functions.
• Develop and validate AI economic models and methods covering cost structures, value realization, unit economics, payback, and scenario analysis. Distinguish initial investment from recurring costs and forecast benefits from measured outcomes.
• Advise CIOs, CFOs, and business leaders on AI portfolio decisions, including build vs. buy choices, deployment options, funding, scaling, and decisions to redesign or discontinue use cases. Clearly explain assumptions, uncertainty, and financial trade-offs.
• Build benchmarks and case studies across horizontal business functions and domain-specific processes. Analyze how adoption, workflow changes, output quality, human oversight, and risk affect cost and realized business value.
• Partner with the sourcing advisory team to incorporate ongoing price benchmarks and commercial terms into economic models, including their impact on cost at scale.
• Produce syndicated and custom research, brief clients, and represent the organization in executive discussions and industry events. Translate evidence from enterprise deployments into clear, defensible research and practical guidance.

Required Qualifications

• Senior practitioner experience leading AI deployments in large organizations, with direct responsibility or defined shared accountability from business case and funding through production, adoption, and post-deployment performance. Ability to explain your own decisions and resulting outcomes.
• Hands-on delivery across multiple distinct business functions or domains, including horizontal corporate workflows and domain-specific operational processes. Examples include finance, procurement, human resources, customer service, and supply chain or industry operations. Experience within one industry is acceptable; multiple projects within one functional silo do not meet the breadth requirement.
• Direct responsibility for AI budgets, forecasts, and investment models covering capital and operating expenditure, cost structures, value realization, unit economics, and sensitivity analysis. Experience tracking actual costs and benefits against forecasts and revising assumptions as adoption and scale change.
• Detailed knowledge of lifecycle costs: data, integration, software and model licensing, compute, implementation, evaluation and monitoring, security and governance, adoption, human oversight, and ongoing support. Ability to model unit cost at different volumes and service levels, and explain the financial implications of AI platform, deployment, and sourcing choices.
• Evidence of measuring and realizing business value. Ability to distinguish cash savings, cost avoidance, capacity released, revenue or margin contribution, and service or risk improvements; establish baselines and benefit owners; and address attribution, timing, and double counting.
• Experience presenting to and advising both CIOs and CFOs on AI investments, funding, operating costs, and realized value, supported by strong working relationships with finance, technology, and business leaders.
• Ability to produce clear research and executive presentations, evaluate financial and operational data, normalize survey and benchmark findings, and turn lessons from individual deployments into defensible models and broader guidance.
• Candidates may come from enterprise operating roles or consulting firms. Consulting candidates must demonstrate hands-on delivery for large enterprise clients, with identifiable responsibility for implementation economics and measurement of results after launch.
• Bachelor’s degree required.

Preferred Qualifications

• Experience publishing research, developing reusable economic models, or advising multiple enterprise clients; experience with generative AI and agentic AI.
• Master’s degree in a relevant field.

Compensation & Benefits

• Expected total annual compensation: between $180,000-$240,000, inclusive of base salary and variable compensation (depending on location and experience).
• If this role relocates to a different country, the salary range will be updated to reflect that country’s range rather than a currency conversion of the original range.

Location and Travel

• This role can be based remotely in an approved U.S. location or at the Boston office.
• Travel of approximately 25–30% is expected.

Remote Eligibility (Approved U.S. States)

Remote workers may be employed in: Arizona (AZ), California (CA), Colorado (CO), Connecticut (CT), Washington D.C. (DC), Florida (FL), Georgia (GA), Illinois (IL), Indiana (IN), Kansas (KS), Massachusetts (MA), Maryland (MD), Maine (ME), Michigan (MI), Minnesota (MN), Missouri (MO), Mississippi (MS), North Carolina (NC), New Hampshire (NH), New Jersey (NJ), New York (NY), Ohio (OH), Oregon (OR), Pennsylvania (PA), Rhode Island (RI), South Carolina (SC), Tennessee (TN), Texas (TX), Utah (UT), Virginia (VA), Vermont (VT), Washington (WA), and Wisconsin (WI).

Additional Information

• Employment eligibility verification is required.
• E-Verify participation applies.