AI and Workflow Analytics Intern (Current Masters or PhD)

Keystone is a premier economics, technology, and strategy consulting firm built to help companies lead through transformation. As breakthrough innovations reshape industries, redefine competition and change our society, complex and highly competitive ecosystems emerge. Keystone advises technology leaders, Fortune 100 companies, their legal counsel, and governments on business, economic, litigation, and regulatory strategy in relation to these innovations and competitive eco-systems. We operate globally from offices in New York, Boston, San Francisco, Seattle, London, Dubai, and Washington, D.C.

About K.AiML

The Keystone Artificial Intelligence & Machine Learning (KAIML) team is building the firm’s AI capabilities from the ground up. We are developing internal tools, enabling teams to use AI in client work, and establishing the governance and infrastructure needed to scale these capabilities across the organization.

We work closely with leading researchers and practitioners on cutting-edge problems at the intersection of AI, economics, and business strategy.

About the Internship

We are seeking a Masters- or PhD-level intern to work on a high-impact, firm-wide initiative to quantify the business value of AI.

As Keystone scales its use of AI tools, we are building a rigorous, data-driven understanding of how work is performed today and how AI changes that work. This role will focus on analyzing internal workflow and time entry data to establish baseline performance and estimate the impact of AI-enabled tools on productivity, efficiency, and quality.

This work will directly inform product development, prioritization decisions, and executive-level strategy.

Key Responsibilities

• Analyze structured and semi-structured internal data (e.g., time tracking, workflows, tool usage)

• Develop models or frameworks to estimate time savings and productivity improvements

• Identify patterns in how work is performed across teams and workflows

• Partner with AI engineers and forward-deployed teams to connect analysis with real-world use cases

• Translate findings into actionable insights for product and leadership decision-making

• Contribute to the development of a scalable framework for measuring AI-driven value across the firm

What You'll Bring

• PhD student in Applied Mathematics, Statistics, Computer Science, Economics, or a related quantitative field

• Strong analytical and modeling skills

• Ability to structure ambiguous problems and produce clear, actionable insights

• Interest in applying quantitative methods in a fast-paced, high-impact environment

• Familiarity with NLP/ML methods for extracting structure from unstructured data (e.g., text classification, clustering, or embedding-based analysis), and comfort working with modern Python-based data science tooling

Why This Role

This is not a traditional research internship. You will work on problems that sit very close to decision-making at the firm level, with direct visibility into how AI is transforming real workflows.

You will have the opportunity to:

• Work on a novel and highly relevant problem: measuring the real impact of AI in knowledge work

• Collaborate with a cross-functional team of engineers, consultants, and leadership

• Contribute to decisions that shape how AI is deployed across the firm

• Gain exposure to cutting-edge applications of AI in consulting, litigation, and strategy

Additional Details

• Duration: Summer 2026 (flexible start/end dates)

• Location: Boston (hybrid)

As an intern, actual compensation within the range will depend upon the level the individual is hired into based on their skills, experience, and qualifications.

Intern Pay Range
$112,000—$140,800 USD

At Keystone we believe diversity matters. At every level of our firm, we seek to advance and promote diversity, foster an inclusive culture, and ensure our colleagues have a deep sense of respect and belonging. If you are interested in growing your career with colleagues from varied backgrounds and cultures, consider Keystone.