Case Study: RMIT School of Psychology — 195% ROI | Real Minds AI

Case Study · Higher Education & Research

From ‘Generation Tool’ to Colleague

RMIT School of Psychology  |  AI Training  |  March 2026

Real Minds AI delivered 8 domain-specific, methodology-first AI training workshops for RMIT University’s School of Psychology: 31 academics, 28 contact hours over 8 weeks (5 February – 26 March 2026), investment $12,800. Researchers shifted from using AI as a “generation tool” to working with it as an error-checking colleague. Documented outcomes: a data-preparation task cut from 8 months to 20 minutes, 200+ pages of reusable research briefs and teaching materials, 3–5 core adopters running 5+ sessions each, and a conservative first-year ROI of 195%. Russell Conduit, Associate Dean (Psychology), attended 7 of 8 workshops and is a named, verified referee. Delivered by Dr Dennis Wollersheim (PhD Computer Science, 53 publications) and Tracy Anthony of Real Minds AI, Melbourne.

At a Glance

ClientRMIT University — School of Psychology (31 academics)
Engagement8 weeks — 5 February to 26 March 2026
Format8 × 4-hour hands-on workshops (28 contact hours; ~180 person-hours delivered)
Investment$12,800
Core adopters3–5 researchers, 5+ sessions each
Legacy200+ pages of reusable research briefs, handouts, decks & transcripts

“I used to use AI to just generate stuff or search for stuff. But now I see it as almost like another colleague where you can bounce ideas off and evaluate and error-check. That’s been the biggest enlightenment for me — I never thought before these workshops of using it that way.”

— Russell Conduit, Associate Dean (Psychology), attended 7 of 8 workshops

The Engagement

The Challenge

  • No domain-specific training — university AI sessions covered prompting basics, not psychology research methods
  • No verification culture — researchers either trusted AI blindly or avoided it entirely
  • No methodology integration — AI used as a search engine, not embedded in research workflows
  • 31 academics with scattered, inconsistent AI relationships across the school

What We Built

  • 8 workshops covering the full arc from mindset shift to reproducible pipelines
  • 11 research briefs synthesising 50,000+ words of peer-reviewed evidence
  • 8 slide decks, 8 exercise handouts, 7 clean transcripts and prompt template packs
  • A unified ResearchOps Loop: Ingest → Structure → Transform → Verify → Ship

The Impact

  • 8 months to 20 minutes — data-extraction code that took 8 months now runs in 20 min
  • 500-paper screen with zero errors across 200 spot-checked papers
  • Teaching multiplier — core adopters now training their own students
  • Conservative Year 1 ROI of 195%+ against the RMAI fee
195%+
Conservative Year 1 Recovery
Against the RMAI engagement fee
200+
Pages of Reusable Materials
Research briefs, handouts, transcripts
28
Hours of Hands-On Training
~180 total person-hours delivered

What Made This Different

Domain-specific, not generic

Every exercise used real psychology research tasks — real transcripts, real ARC criteria, real PICO frameworks. Researchers learned to integrate AI into methodologies they had already mastered.

Methodology-first, not tool-first

We started with “here’s what your research needs,” not “here’s what the tool can do.” Epistemological limits came first; practical application followed.

Honest about failures

We demonstrated 20% citation error rates live. We showed emotion sanitisation in qualitative data. We triggered automation bias on purpose — building trust through transparency.

Materials as institutional legacy

200+ pages of briefs, handouts, decks and transcripts available to all 31 academics — including those who didn’t attend. The long tail extends years beyond the program.

The Bigger Picture

Most AI training teaches people which buttons to press. The shift that matters — the one Russell named — is moving from treating AI as a generation tool to treating it as a colleague you can reason with, challenge, and error-check.

That shift doesn’t come from a tool demo. It comes from working through your own real tasks, with someone who knows both the technology and the limits of trusting it. For a research school, the payoff compounds: the people we trained are now training their students, and the materials outlast the engagement.

Training a research team or faculty?

If your people are stuck using AI as a search engine — or avoiding it because they don’t trust it — we run domain-specific, methodology-first training that changes how they work. One conversation is all it takes to scope it.

Let’s Have a Conversation or call 0480 032 916

Case study published with client approval. Full documentation and evidence available on request.

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