Empowering Government Productivity: Key Takeaways from the Microsoft 365 Copilot Trial🚀

Earlier this year, the Australian Public Service (APS) completed a six-month, whole of government trial of Microsoft 365 Copilot, spanning January–June 2024. Over 7,700 licenses were issued across nearly 60 agencies, engaging more than 2,000 staff in exploring the benefits, challenges, and future role of generative AI within government workflows digital.gov.audigital.gov.au.

• Strong optimism and uptake: After the trial, 77 % of participants expressed a positive view of Copilot, with 1 in 3 using it daily digital.gov.au.
• Targeted training matters: Participants receiving 3+ training sessions reported 75 % confidence in using Copilot—28 points higher than those with minimal training digital.gov.au.
• Productivity gains: APS staff saved ~1 hour/day on summarising, drafting, and research-intensive tasks, leading ~40 % to reallocate time to higher value work digital.gov.au.
• Senior endorsement: Senior executives displayed the greatest enthusiasm (93 %), underscoring leadership buy in digital.gov.au.
• Majority want more: A resounding 86 % wish to continue Copilot use post-trial digital.gov.au.

• Stigma & trust issues: Cultural resistance and concerns over accuracy and ethics hindered fuller uptake digital.gov.audigital.gov.au.
• Legal/Governance grey areas: Uncertainty around accountability, disclosure rules (e.g. for meeting transcriptions), and compliance frameworks slowed adoption digital.gov.au.
• Integration hurdles: Copilot’s limitations with third party software—such as Janus seal data labelling and JAWS accessibility—were flagged as key issues digital.gov.au.
• Equity concerns: Risks of skill erosion, gendered impacts on administrative roles, and cultural bias in outputs (e.g. First Nations content) were highlighted digital.gov.au.

• Adaptive governance needed: The fast-evolving nature of generative AI demands agile risk frameworks and continuous policy updates digital.gov.audigital.gov.au.
• Setup is critical: Agencies must secure systems, permissions, and network configuration to support AI safely digital.gov.au.
• Monitor real world impact: Ongoing evaluation of workforce effects and unintended consequences is essential digital.gov.au.

1. Choose tools deliberately —align generative AI options with organisational environment and use cases.
2. System configuration —ensure secure, compliant setup and seamless integration.
3. Customise training —focus on role specific prompts and scenarios; identify internal champions.
4. Change management —equip leaders to champion adoption and share success stories.
5. Map workflows —identify where AI adds real value and replicate use cases across teams.
6. Facilitate sharing —create inter-agency forums to share insights and lessons.
7. Track impacts —deploy metrics and workforce monitoring to manage emerging risks.
8. Clarify accountabilities —define consent, disclaimers, and legal responsibilities upfront digital.gov.au.

At Cadmus, we see these findings as a blueprint for effective Generative AI adoption:

• Focus on real team needs: Prioritise training and apply AI to targeted workflows—Citizens, analysts, administrators.
• Lead with governance: Design hybrid frameworks framing AI’s legal, ethical, and access implications. Stay dynamic.
• Promote pilot success: Share early wins via internal champions to build trust and reduce stigma.
• Invest in oversight: Monitor employee engagement, productivity metrics, and societal impacts. Be proactive.

The APS Copilot trial proves generative AI can deliver significant productivity improvements—but only when adoption is well structured. With thoughtful governance, robust training, and ongoing evaluation, generative AI can be responsibly and effectively rolled out in public sector and private-sector environments alike.