Evidence
The sprint is grounded in real workplace pressures: AI adoption, privacy risk, psychosocial risk, performance ambiguity, consultation obligations and responsible AI expectations.
Source
Microsoft and LinkedIn Work Trend Index
75%
What it says
Microsoft and LinkedIn report widespread AI use by knowledge workers.
P&C consequence: managers need practical guidance because AI use is already inside daily work.
Source
OAIC generative AI privacy guidance
Privacy
What it says
Privacy obligations apply when personal information is input into AI systems or appears in AI outputs.
P&C consequence: employees and managers need practical guidance on what information must not be entered into AI tools.
Source
Safe Work Australia psychosocial hazards
WHS
What it says
Work design, job demands, support, role clarity and change management can create psychosocial risks.
P&C consequence: AI change can affect workload, ambiguity, supervision, monitoring concerns and employee trust.
Source
Fair Work Ombudsman performance guidance
Fair process
What it says
Performance issues require clear communication, support and appropriate process.
P&C consequence: managers need guidance on whether poor AI-assisted work is a capability, conduct, quality or training issue.
Source
Australian Voluntary AI Safety Standard
10
What it says
The Australian AI safety guardrails include accountability, risk management, human oversight, transparency, records and stakeholder engagement.
P&C consequence: responsible AI expectations need to become manager guidance, employee communication and escalation pathways.
Source
Digital NSW AI Assessment Framework
AIAF
What it says
The NSW AI Assessment Framework is used by NSW Government agencies to assess and govern AI use cases.
P&C consequence: organisations may need people-side evidence that expectations, oversight and communication are in place.
This page connects sources to practical P&C consequences. It does not provide legal advice or replace specialist employment, privacy, WHS, cyber or regulatory advice.