Virtual
Virtual Talk / 45-Minute Lecture
Starting at $2,500. Most engagements in this format fall in the $2,500-$4,000 range.
This is my entry rate for campus virtual events and small consortia.
Speaking & Workshops
Paid talks, workshops, and lecture-demos on AI
I speak for colleges, universities, professional associations, and selected organizations that want technically grounded, non-hype guidance on AI. If you need a keynote-style talk, a faculty workshop, or a live lecture-demo that shows what current systems can actually do, this is paid speaking work with published starting rates.
Formats and Starting Fees
These are planning ranges, not fixed quotes. Final pricing depends on audience, level of customization, scheduling, and travel.
In Person
Campus Lecture or Short Workshop
Starting at $5,000. Most engagements in this format fall in the $5,000-$7,500 range.
Best for keynote-style campus talks, invited lectures, and shorter workshop sessions. Travel costs are additional.
Half-Day
Half-Day Workshop or Lecture-Demo
Starting at $7,500. Most engagements in this format fall in the $7,500-$12,000 range.
This is the right format when you want live demonstrations, hands-on discussion, or a longer faculty or leadership session. Travel costs are additional.
Corporate
Corporate Engagements
Contact for pricing.
Corporate talks, internal training, and strategy sessions are quoted separately based on scope, audience size, and use case.
Selected Testimonials
Client Feedback
“Professor Bachman’s AI webinar was great! Our clients learned a lot and appreciated Dave’s accessible introduction to the world of AI.”
Donald P. Gould
Gould Asset Management LLC
Client Feedback
“THANK YOU! For your exceptional presentation. To a moment, it was pitch perfect and precisely the material they wanted to learn. You were the buzz of the week.”
Jill Klein
Jill Klein Advisors LLC
Client Feedback
“David is exactly the kind of expert you want when navigating the complexities of artificial intelligence. During our panel on AI Coding Competencies, his strategic insights were invaluable. He has a rare gift for making the future of AI accessible and actionable. A tremendous speaker and a clear authority in his field.”
Isaac Sacolick
StarCIO, Bestselling Author, & Host of
Coffee With Digital Trailblazers.
Recent and Upcoming Events
(Re)Imagining Education in the Age of GenAI
Co-organizer and workshop leader. Harvey Mudd College, May 2026.
AI-Assisted Coding
Workshop leader. Integrating Research and Illustration in Number Theory conference, Institut Henri Poincaré, Paris, March 2026.
AI Coding Competencies
Panelist. Coffee with Digital Trailblazers, April 2026.
About David Bachman
I am a Professor of Mathematics at Pitzer College, where I teach mathematics, computer science, and data science. I hold a PhD in mathematics, have published more than 20 papers, and have received NSF support for my research. I am also the author of three books, including Advanced Calculus DeMYSTiFieD, published by McGraw-Hill. I recently co-organized a trimester program on mathematical illustration at the Institut Henri Poincaré in Paris, where I also led a workshop on AI-assisted coding for research mathematicians. In addition to my academic work, I write publicly about AI and the future of higher education and work at my Substack, Entropy Bonus. Each week I also build a new application with AI coding tools and write about what this process reveals about the current state of the technology.
Canned Talks and Lecture-Demos
These are the talks I give most often. Each can be tuned for a keynote, a campus lecture, a workshop, or a leadership session.
Lecture-Demo
What AI Can Actually Build: Live Demos from a Mathematician's Workshop
A live demonstration session built around software, visual tools, and small applications I have made with AI systems. The point is not spectacle. It is to give the audience a concrete model of what current systems can build, how much guidance they require, where they fail, and what kinds of expertise still matter.
Target audience: Faculty, academic leaders, innovation teams, professional associations, and skeptical general audiences who want a reality-based picture of current AI capability.
Takeaways: A more accurate capability model, a clearer sense of the line between prototype and production, and concrete examples of what AI-assisted building looks like in practice.
Campus Talk
AI Literacy After the Hype Cycle
A practical overview of how contemporary AI systems work, what they are good at, where they reliably break down, and what institutions actually need from an AI literacy program. This talk is designed to move audiences past both panic and boosterism.
Target audience: Faculty, staff, administrators, students, and campus communities that need a shared baseline understanding of AI.
Takeaways: A common vocabulary, a more stable model of current systems, and a clearer sense of what responsible adoption should look like.
Faculty Workshop
AI, Assessment, and Academic Integrity After the Panic
This session looks at what actually changed once generative AI became widely available, why many reactive responses were structurally weak, and what more durable assessment design looks like now. The emphasis is on redesign, not policing.
Target audience: Faculty groups, teaching centers, deans, department chairs, and academic policy committees.
Takeaways: Better assessment options, a more realistic view of academic-integrity enforcement, and clearer criteria for when AI use should be restricted, incorporated, or explicitly taught.
Curriculum
What a Serious University AI Curriculum Should Include
A talk about what students should actually learn if an institution wants to move beyond surface-level prompt training. I outline the conceptual foundations, technical topics, ethical framing, and project work that make an AI curriculum intellectually serious and durable.
Target audience: Curriculum committees, faculty in computer science and data science, liberal arts faculty, and academic leaders planning new programs.
Takeaways: A clearer model of core AI-literacy outcomes, a sharper distinction between tool fluency and real understanding, and a stronger basis for course and program design.
Leadership
Designing an Institutional AI Strategy That Will Still Make Sense Next Year
A leadership-focused session on how to respond to AI without building policy around headlines or vendor pressure. The talk addresses governance, procurement, experimentation, training, and the difference between symbolic planning and operational planning.
Target audience: Presidents, provosts, CIOs, deans, boards, and leadership teams responsible for institution-wide planning.
Takeaways: A more durable planning framework, a better sense of where central coordination is needed, and clearer next steps for policy, training, and implementation.
Why organizations bring me in
The goal is not generic AI enthusiasm. It is to give audiences a clearer model of what current systems can do, where they fail, and how an institution or professional community can respond without confusion, panic, or empty slogans.
- Help audiences understand what current AI systems can and cannot do.
- Give faculty, leaders, and professionals a clearer basis for decisions.
- Use live demonstrations to make abstract claims concrete.
- Leave teams with next steps that fit their audience and context.
How booking works
Most bookings begin with a short email exchange or a brief call about audience, format, timing, and the level of technical depth you want. From there I recommend the best talk or workshop format, confirm a starting range or custom quote, and send a simple agreement. Once booked, I tailor the session to your context and coordinate any live-demo or AV needs in advance.
Most engagements book 2-4 months in advance, though I can sometimes accommodate shorter timelines.
You can also download a one-page overview to share with your team.