STUDIO · CONTENT CURRENCY
AIB102 Bachelor Degree Current
Critical AI Literacy
Credit points: 6cp. Last updated 25 Jul 2026.
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INDEXING UNIT 150 lessons · 6 modules · 56 assessments
Continuous Curriculum Improvement Scanner
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W
Web Crawler
Web and policy sources
crawling
connect: arxiv.org, industry.gov.au, hbr.org
Australian Bureau of Statistics: business activity (2026)
nature.com/articles/s41586 (cited)
industry.gov.au: Safe and Responsible AI (2026)
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Scholar Index
Peer reviewed literature
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Harvard Business Review (2026)
Chen et al., Nature Machine Intelligence (2026)
match: AIB102 / 4.4 ROI evidence base (0.94)
agentic AI corpus: 412 papers indexed
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Live Feed
Real time news and industry
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engage: real time web, news feed
enterprise deployment trends (2026)
Baker and Beaufort, Science (2026)
match: AIB102 / 1.6 workplace examples
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query: Scopus, Web of Science, ProQuest
MIT Sloan Management Review (2026)
OECD Behavioural Insights Toolkit (2026)
match: AIB102 / 3.6 prompting versus RAG
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Updates needed (3) All lessons (150)
MODULE 1 What is AI?
1.6 Where AI is used in business today Update Available
MODULE 3 Generative AI Foundations
3.6 Fine tuning versus prompting versus RAG Update Available
MODULE 4 AI in Business Strategy
4.4 ROI frameworks for AI investments Update Available
Showing 3 lessons across 3 modules in this unit. The other 147 need nothing.
Lesson 4.4: ROI frameworks for AI investments
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Standard ROI frameworks assess four dimensions: cost reduction, revenue uplift, faster time to market, and strategic optionality.

In 2026, the evidence base for AI ROI has matured considerably. Organisations with strong AI deployments report an average 3.7 times return per dollar invested, with top performers achieving over ten times returns.

The most reliable gains are in document drafting, software engineering and customer correspondence.

SUGGESTED UPDATE ADDED

Standard ROI frameworks assess four dimensions: cost reduction, revenue uplift, faster time to market, and strategic optionality.

In 2026, the evidence base for AI ROI has matured considerably. Returns are highly skewed. A small group of leaders captures disproportionate value, while many organisations report modest or unmeasurable returns. The best predictors are governance maturity, use case specificity and workflow redesign (Harvard Business Review, 2026). Australian evidence remains limited.

The most reliable gains are in document drafting, software engineering and customer correspondence.

HBR
Harvard Business Review (2026)
Seven factors that drive returns on AI investments, according to a new survey.
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2.3
Defining machine learning
Now fully covered in 1.2 What is AI
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5.1
Early prompt engineering patterns
Superseded by 3.6 Prompting versus RAG
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7.4
Vendor landscape 2024
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