Vice President Research, AI Planning and Operations

United StatesRemoteFull-timeexecutive

OtherPresident

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Requirements Summary

Bachelor's degree required; a master's degree in a relevant field is preferred. Senior practitioner experience leading AI deployments within large organizations,

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OtherPresident

This senior leadership role focuses on helping enterprise organizations understand the economics of artificial intelligence and make informed investment decisions.
You will bring hands-on experience from large-scale AI deployments into independent research, financial modeling, and executive advisory work.
The role spans AI investment prioritization, budgeting, forecasting, cost management, and business value realization.
You will develop practical economic models that account for both initial investments and ongoing operating costs.
You will advise CIOs, CFOs, and business leaders on scaling, sourcing, funding, and portfolio decisions.
The position combines research, quantitative analysis, executive communication, and industry engagement in a highly collaborative environment.
It can be performed remotely from an approved U.S. location or from a Boston office, with approximately 25–30% travel expected.

Contribute to research on enterprise AI economics, covering investment prioritization, budgeting, forecasting, cost structures, and value realization across business functions and use cases.
Develop and validate AI economic models addressing total lifecycle costs, unit economics, payback periods, scenario analysis, and realized business value.
Advise CIOs, CFOs, and business leaders on AI portfolio decisions, including build-versus-buy strategies, deployment models, funding, scaling, and decisions to redesign or discontinue use cases.
Build benchmarks and case studies across corporate functions and industry-specific processes, assessing adoption, workflow changes, output quality, human oversight, risk, costs, and business outcomes.
Partner with sourcing specialists to incorporate pricing benchmarks and commercial terms into economic models and assess their impact at scale.
Produce syndicated and custom research, executive presentations, client briefings, and practical guidance grounded in evidence from enterprise AI deployments.
Represent the research function in executive discussions and industry events, translating complex financial and operational findings into clear, defensible recommendations.
Evaluate financial and operational data, normalize survey and benchmark findings, and turn individual deployment experiences into reusable models and broader research insights.

Requirements

~2 min read

Bachelor's degree required; a master's degree in a relevant field is preferred.
Senior practitioner experience leading AI deployments within large organizations, with direct responsibility or defined shared accountability from business case development and funding through production, adoption, and post-deployment performance.
Hands-on experience across multiple business functions or operational domains, such as finance, procurement, human resources, customer service, supply chain, or industry-specific processes.
Demonstrated ownership of AI budgets, forecasts, investment models, capital and operating expenditures, cost structures, value realization, unit economics, and sensitivity analysis.
Strong understanding of AI lifecycle costs, including data, integration, licensing, compute, implementation, evaluation, monitoring, security, governance, adoption, human oversight, and ongoing support.
Ability to model unit costs across different volumes and service levels and explain the financial implications of AI platforms, deployment approaches, and sourcing decisions.
Proven experience measuring business value, including cash savings, cost avoidance, released capacity, revenue or margin contribution, service improvements, and risk reduction.
Experience establishing baselines and benefit ownership while addressing attribution, timing, and potential double counting.
Strong track record advising CIOs, CFOs, and senior technology and business leaders on AI investment, funding, operating costs, and realized value.
Excellent research, analytical, financial modeling, writing, and executive presentation skills, with the ability to communicate complex findings clearly.
Consulting candidates should demonstrate hands-on delivery for large enterprise clients, including identifiable responsibility for implementation economics and post-launch measurement.
Preferred experience includes publishing research, developing reusable economic models, advising multiple enterprise clients, and working with generative AI or agentic AI.
Ability to work remotely from an approved U.S. location or from the Boston office and travel approximately 25–30% as required.