Episode Overview
Arlene Williams, Associate Deputy Minister, Chief Digital Officer and Clay Bates, Executive Director, AI & Cloud Engineering, both from the Department of Cyber Security and Digital Solutions, Government of Nova Scotia, share how Nova Scotia is turning AI into a practical, trusted capability inside government—starting with secure tools like Copilot, building staff readiness, and keeping public trust front and centre. They also highlight Nova Scotia-built services (like the “Scotty” digital assistant) and the guardrails that keep AI accountable.
Key Themes
- Trust + accountability first: AI can speed work up, but humans stay responsible.
- Practical adoption: start with secure, approved tools in platforms staff already use.
- In-house capability: build and sustain AI-enabled services internally (not just outsource).
- Guardrails + governance: privacy/security rules, existing reviews, and clear boundaries for use.
- Fix the work, not just the tool: AI won’t repair broken processes—it can just accelerate them.
What You’ll Learn
1) From AI Potential to AI Practice
Why “AI is everywhere” isn’t the point—and what it looks like when government uses AI deliberately for better public outcomes.
2) Public Trust as the North Star
Why trust is the public sector’s currency, and how AI use directly impacts that trust.
3) Why Nova Scotia Started with Microsoft Copilot
How deploying AI inside familiar platforms (Microsoft 365) reduces friction and supports day-to-day work.
4) Practical Productivity Use Cases (Without Automating Accountability Away)
How AI can support briefing notes, speaking notes, summarisation, and background research—without becoming the final decision-maker.
5) How Nova Scotia Decides Where Copilot Creates Real Value
How the team looks for repeatable, document-heavy work that can free up capacity and improve service outcomes (not just save minutes).
6) Adoption and Training as Core Infrastructure
Why licensing alone doesn’t create value, and how leadership training and safe “hands-on” environments drive responsible use.
7) Building AI Services In-House: “Scotty”
How Nova Scotia built its own AI-powered digital assistant on NovaScotia.ca as a “front door” to government information—and why owning the capability matters.
8) Internal AI Agents for Operations (Service Desk Example)
How an AI agent can surface fragmented knowledge, triage low-complexity questions, and improve first-contact resolution—while encouraging better data hygiene.
9) Responsible Use Guardrails: Privacy, Security, Governance, Human Accountability
What staff can and can’t do with public gen AI, when approved tools apply, and why AI doesn’t skip standard government controls (PIAs, TRAs, architecture reviews, etc.).
10) Preparing for Agentic AI Without Rushing
Why more autonomous AI increases the need for governance (not decreases it), and how Nova Scotia is thinking about sustainable adoption over speed.
Key Takeaways
- AI in government must be intentional: outcomes first, tools second
- Public trust requires transparency, clear ownership, and explainable outcomes
- AI supports decisions, it doesn’t make them—humans stay accountable
- Starting with secure, familiar platforms (like M365) reduces friction and supports adoption
- Training and leadership enablement are essential for safe, consistent use
- AI doesn’t fix broken processes—without redesign, it just creates faster complexity
- Internal capability (building and sustaining products) reduces reliance on external support and improves responsiveness
- Agentic AI raises the bar for governance—move forward, but do it sustainably
Why You Should Listen
This episode is for public sector leaders, digital and service delivery teams, cybersecurity and privacy professionals, and AI enablement teams who want a grounded view of what responsible AI adoption looks like in practice. It’s especially useful if you’re trying to scale AI across a workforce while protecting privacy, maintaining accountability, and delivering measurable improvements to services.
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