AI Fellow (Part-time)

The Role

Most firms talk about AI. Few have a concrete plan to build it into how they work. Intrinsic is in the second group.

We are at an inflection point: strong AI tools exist, our team is ready to adopt them, and the gap between where we are and what is possible is genuinely closeable. This fellowship exists to close that gap. You will work directly with senior leadership to translate our AI roadmap from ideas into deployed, functioning workflows — tools our deal teams, advisory practitioners, and support functions will use every day.

This is not a research role or a sandbox project. The work is applied, and the outcomes are real. By the end of the program, you will have built and deployed AI agents, documented workflows that outlast the fellowship, and left Intrinsic measurably more capable than when you arrived. If that kind of tangible, firm-wide impact sounds like the right way to spend a summer, keep reading.

Why Intrinsic

• Direct access to senior leadership — you will work alongside the people setting the AI strategy, not in a separate intern track
• Real deployment authority — the tools you build will be used by practitioners on live engagements
• A firm that moves fast and operates lean — your contributions will be visible, attributed, and consequential
• Exposure to middle-market M&A and professional services — a high-value context for understanding how AI can transform knowledge-intensive work
• Participation in the Colorado Thrives AI Fellows cohort — a peer learning and development experience alongside other fellows across Colorado
• A network that extends beyond the fellowship — strong performance here creates lasting professional relationships

What You'll Do

AI Roadmap Execution

• Execute the firm’s AI implementation roadmap in partnership with senior leadership, prioritizing high-impact, practical use cases
• Translate AI ideas from internal brainstorming materials into operational outputs: documented workflows, prototypes, and deployed agents on designated platforms (Microsoft Copilot, Claude, and others)
• Prototype, test, deploy, and iteratively improve AI-enabled tools and workflows that enhance internal efficiency, consistency, and scalability
• Support refinement of existing AI agents and automation workflows through structured testing, performance evaluation, and user feedback

Deal Team & Practice-Specific AI Applications

• Map existing due diligence workflows — Quality of Earnings analysis, data room management, report drafting, management Q&A prep — and identify where AI can reduce manual effort without compromising output quality
• Build and maintain a prompt library for Transaction Advisory Services (TAS) and Finance and Accounting Advisory Services (FAAS) practitioners: tested, documented prompts for common analytical tasks, including financial statement summarization, variance explanation, and diligence narrative drafting
• Develop AI-assisted document review workflows for financial due diligence — extracting structured data from target company financials, payor contracts, and other diligence materials
• Prototype tools that support report generation: section drafts, exhibit labeling, and executive summary structuring that practitioners can review and refine rather than build from scratch
• Assess AI applicability to FAAS workflows, including technical accounting research, ASC 805 documentation support, and client deliverable templating

Adoption, Training & Documentation

• Test AI tools and support team members in learning and adopting existing AI platforms, meeting practitioners where they are rather than assuming baseline familiarity
• Develop internal documentation, playbooks, and templates that make AI tools accessible and replicable firm-wide — not dependent on any one person’s knowledge
• Facilitate internal knowledge-sharing sessions — lunch-and-learns, walkthroughs, and Q&A — that build practical AI fluency across practice areas
• Create a living FAQ and troubleshooting guide for internal AI platforms that reduces friction and builds team confidence

Evaluation, Risk & Governance

• Assist leadership in evaluating new AI use cases for feasibility, risk, and expected business impact prior to implementation
• Develop a lightweight framework for assessing AI tool risk in a client-facing professional services context: accuracy requirements, confidentiality exposure, and output review protocols
• Flag potential risks associated with AI use in client deliverables and recommend