We're Hiring

Research Assistant – Enterprise AI Architectures and Service as a Software TAMs

Join us for an innovative study at the intersection of AI technology and economic modeling.

Key Information

Position Title:
Research Assistant – Enterprise AI Architectures and Service as a Software TAMs
Reports To:
Research Lead (Vernon Keenan) and Principal Investigator (Prof. Abhishek Nagaraj)
Location:
UC Berkeley Haas School of Business and remote work as required

Overview

We are seeking two highly motivated Research Assistants to support an innovative study examining Overlay vs. Embedded AI architectures and the Total Addressable Market (TAM) for Service as a Software (SaaS) models and Virtual Employees (VEs). This project is a collaboration between Keenan Vision and UC Berkeley Haas School of Business, combining technical architecture analysis with economic modeling to uncover the market dynamics and value creation potential of enterprise AI solutions.

Research Assistants will conduct interviews, collect data, and contribute to economic modeling and TAM calculations for Service as a Software. They will play a key role in identifying factors influencing the adoption of AI architectures and quantifying the overall VE TAM, ensuring that this research establishes a new benchmark for evaluating the economics of enterprise AI.

Responsibilities

Interview and Data Collection:

  • Conduct structured interviews with:
    • Executives at Overlay AI companies.
    • Embedded AI vendors and their enterprise customers.
    • Stakeholders in the emerging Service as a Software and VE ecosystems.
  • Gather insights on market opportunities, implementation patterns, and adoption challenges.

TAM Research and Modeling:

  • Collect and analyze data to define the Total Addressable Market (TAM) for:
    • Service as a Software business models.
    • Virtual Employee (VE) solutions in enterprise contexts.
  • Identify industry-specific TAM segments, customer needs, and growth projections.

Architectural and Economic Analysis:

  • Assist in documenting distinctions between Overlay and Embedded AI architectures, including metadata, security models, and scalability.
  • Apply VE Economics principles (Infinite Scale, Cognitive Commoditization, Exponential Learning) to evaluate how these architectures impact market dynamics.

Database Management:

  • Build and manage a comprehensive database of interview responses, market data, and case studies for both architectural approaches and VE TAM projections.
  • Ensure consistency and accuracy across datasets for use in research publications and presentations.

Collaboration and Reporting:

  • Work closely with the Research Lead, Principal Investigator, and other team members to refine analysis frameworks.
  • Participate in team workshops and contribute findings to the creation of economic models, case studies, and recommendations.
  • Draft sections of the final research paper, particularly those related to TAM modeling and Service as a Software opportunities.

Qualifications

Academic Background:

  • Current graduate student or recent graduate in Business, Economics, Data Science, Computer Science, or related fields.
  • Knowledge of AI technologies, enterprise software, or TAM modeling is preferred.

Skills and Experience:

  • Strong communication skills for conducting interviews with industry professionals.
  • Analytical mindset with experience in market research and economic modeling.
  • Proficiency in tools for data analysis and visualization (e.g., Excel, Tableau, or R/Python for TAM analysis).
  • Familiarity with enterprise AI technologies and the SaaS business model is a strong advantage.

Personal Attributes:

  • Highly organized and detail-oriented.
  • Collaborative, with the ability to work in a dynamic, cross-disciplinary team.
  • Passionate about enterprise AI and its transformative potential in modern economies.

Benefits

  • Gain hands-on experience in cutting-edge AI and market research.
  • Participate in defining new TAM benchmarks for Service as a Software and VE Economics.
  • Network with industry leaders and academic pioneers in enterprise AI.
  • Contribute to high-impact research with real-world applications in enterprise decision-making.
  • Opportunity to co-author academic publications or industry white papers.

Application Process

Interested candidates should submit the following:

  • A resume detailing relevant experience.
  • A cover letter explaining their interest in the position and the research topics.
  • A writing sample or portfolio of relevant work, if available.
Apply Now via Contact Page

Please use the subject line: "Application: Research Assistant AI Economics" when contacting us.