AI Competitors

AI Venture Velocity Challenge

Accelerating Evidence-Based Venture Progress with AI

The AI Venture Velocity Challenge rewards disciplined experimentation, rapid learning, and intelligent use of AI to accelerate venture progress.
While teams present at multiple stages, advancement decisions are grounded in documented experimentation and measurable progress, not presentation polish alone.

Why Venture Velocity Matters Now

Today’s strongest entrepreneurs are building companies faster and more efficiently by leveraging AI to accelerate customer discovery, prototyping, analysis, and iteration.

In an AI-enabled world, competitive advantage increasingly comes from:

  • Identifying meaningful, high-impact problems worth solving
  • Prioritizing the most critical assumptions
  • Designing disciplined experiments
  • Learning faster than competitors
  • Making evidence-based decisions quickly

The AI Venture Velocity Challenge rewards founders who demonstrate this capability.

Prize funding is intended to accelerate ventures that have already demonstrated rapid, evidence-based learning and responsible execution.

Call for Submissions

Texas A&M University’s Mays Business School invites individuals and teams of undergraduate and graduate students nationwide to apply.

From all eligible submissions, judges will select the Top 24 ventures to advance to a virtual review round. From those, the top 12 will advance to the in-person finals in College Station.

Submissions are Open

Submissions are due by 11:59 p.m. CDT on May 1, 2026.

How the Competition Works

Stage 1: Venture Snapshot and Experimentation Blueprint

Due May 1, 2026
Teams submit a structured Venture Snapshot, including:

  • Clear articulation of the problem and opportunity
  • Starting point snapshot (venture stage and baseline traction)
  • 3–5 highest-risk assumptions
  • Experimentation roadmap
  • Planned use of AI to accelerate learning

Submissions should clearly establish both the significance of the opportunity and the key assumptions that must be tested for the venture to succeed.

This replaces a traditional written business plan.

MVP is not required at the initial submission.

Stage 2: Learning Progress Review (Top 24)

Virtual Round – July 1, 2026
Selected teams present:

  • Experiments conducted since May
  • Evidence gathered
  • Key learnings and pivots
  • MVP or prototype evolution
  • AI-enabled acceleration

The top 24 teams will be required to demonstrate meaningful product or solution progress, including an MVP or working prototype where applicable.

Advancement is based on documented learning velocity and progress relative to the starting point.

Stage 3: AI Venture Velocity Finals (Top 12)

In-Person – Sept. 25–26, 2026 | College Station, TX
Finalists compete based on:

  • Cumulative Experiment Log
  • Demonstrated uncertainty reduction
  • Venture progress
  • Responsible impact and ethical design
  • Adaptive execution

Final winners are selected using the same criteria.

Required Experiment Log

All teams must maintain a structured Experiment Log documenting their learning throughout the competition period.

After submitting their Venture Snapshot, all applicants will receive a link to the official Experiment Log submission form.

Each experiment entry must include:

  • Hypothesis tested
  • Why the assumption matters
  • Experiment design
  • AI used (if applicable)
  • Evidence collected
  • Decision made
  • Impact on venture direction

Entries are time-stamped and serve as the official record of learning velocity.

Advancement at each stage is determined by rubric scoring and documented Experiment Log evidence demonstrating continued progress on the most important assumptions using AI to accelerate learning and decision-making.

Eligibility

  • All individuals and teams must be students currently enrolled at an accredited U.S. university.
  • Students from all majors are eligible to participate.
  • Entries must leverage AI technologies as a core component of the venture.
  • Individuals and teams must demonstrate ownership or full rights to any technology or intellectual property used.
  • Ventures cannot have generated more than $5 million in gross revenue in any 12-month period prior to Jan. 1, 2026.

Evaluation Criteria: AI Venture Velocity Challenge

Teams will be evaluated using the following rubric:

Problem Significance and Opportunity Quality (25%)

Problem Importance:

Does the venture address a meaningful, clearly defined problem with material business or societal relevance?

Customer Understanding:

Is there evidence that the problem is real and validated with target customers?

Market Opportunity:

Is the opportunity attractive in size and scope, with a clear target segment and value proposition?

Learning Velocity and Experimentation Rigor (30%)

Hypothesis Clarity:

Has the team identified the most important assumptions underlying the venture?

Experiment Design Quality:

Are experiments thoughtfully designed to test the highest-risk assumptions?

Evidence-Based Decisions:

Does the team use data and results to inform pivots, refinements, or strategic direction?

Speed of Iteration:

How quickly and systematically does the team test, learn, and iterate?

AI Integration & Leverage (20%)

AI as a Learning Accelerator:

How effectively are AI tools used to accelerate research, experimentation, prototyping, analysis, or discovery?

AI as a Solution Enabler (if applicable):

Does AI meaningfully enhance the product or service?

Intentionality and Appropriateness:

Is AI applied thoughtfully and strategically rather than superficially?

Evidence of Venture Progress (10%)

Progress Relative to Starting Point:

Has the venture made measurable progress during the competition window?

Uncertainty Reduction:

Have critical risks and assumptions been clarified or resolved?

Forward Momentum:

Is the venture demonstrating increasing clarity and direction over time?

Responsible Impact & Ethical Design (10%)

Societal Contribution:

Does the venture address important challenges and contribute positively to customers or communities?

Responsible AI Practices:

Does the team demonstrate awareness of ethical considerations such as privacy, bias mitigation, transparency, and governance?

Long-Term Impact Awareness:

Has the team considered potential unintended consequences and responsible scaling?

Adaptive Execution & Coachability (5%)

Responsiveness to Evidence:

Does the team adjust when data contradicts assumptions?

Decision Discipline:

Is decision-making clear and coherent?

Team Agility:

Does the team work cohesively and respond constructively to feedback?

Scoring Guidelines

Each criterion will be scored on a scale of 1 to 5:

1 – Poor: Element absent or inadequately addressed.
2 – Fair: Present but underdeveloped or lacking supporting evidence.
3 – Good: Adequately addressed with reasonable documentation.
4 – Very Good: Well-developed and evidence-based.
5 – Excellent: Exceptional, rigorously supported by documented experimentation and learning

Awards

The competition will award $400,000 in cash prizes:

1st Place: $250,000

2nd Place: $100,000

3rd Place: $50,000

Additional benefits include:

  • Mentorship Opportunities: Winners may be paired with an Aggie entrepreneur mentor for one year.
  • Travel Assistance: Top 12 teams will receive funding to support travel for two presenters to College Station.

Submission Deadline:
May 1, 2026, by 11:59 p.m. CDT.

Contact:
Please direct any inquiries with the subject line “AI Venture Velocity Challenge” to aicompetitions@mays.tamu.edu.

AI Dissertation Proposal Competition

The AI Dissertation Proposal Competition recognizes doctoral students whose research advances the intersection of artificial intelligence, business, and society.

Evaluation emphasizes:

  • Research rigor
  • Scholarly contribution
  • Practical relevance
  • Responsible AI considerations

Details and submission requirements are provided separately for this track.