Deploying AI Agents? Start With Data Discipline
AI tools vary widely in complexity. Basic AI, like summarising emails or generating meeting notes, can be deployed with minimal preparation. These tools are often plug-and-play, requiring little more than user access and a browser. But as agencies move toward more sophisticated AI agents – those that make decisions, interact with systems, or handle sensitive data – the stakes rise dramatically.
Sophisticated AI agents are not just tools; they’re operational actors. They need access to structured data, integration with internal systems, and the ability to execute tasks. That means they must be governed like any other privileged system. In the federal government context, this includes alignment with PSPF, ISM, and various agency-specific data handling protocols.
Data discipline starts well before you’re deploying an AI agent. Good quality, well-understood, trusted data is key to both training models and setting up agents. The old adage holds true here – garbage in, garbage out! Without proper governance, these agents can pose real risks. They might access data they shouldn’t, make decisions without audit trails, or expose sensitive information. Worse, they could undermine public trust if their actions aren’t transparent or accountable.
We’ve all known for years that good data underpins smooth operations, but we’ve been able to paper over it with hard-working front-line staff. To deploy AI agents we need to move past these band-aids and fix the underlying data issues.
To deploy advanced AI responsibly, agencies must invest in data quality, data governance, management, and security. That includes:
- Data classification & metadata: Know what data the AI is accessing.
- Access controls: Ensure only authorised agents can interact with sensitive systems.
- Auditability: Maintain logs of AI actions for review and compliance.
- Training and awareness: Equip staff to understand the capabilities and limits of AI tools.
AI is not one-size-fits-all. The governance required depends on the complexity and sensitivity of the use case. Agencies that get this right will unlock powerful capabilities – without compromising security or integrity.
If you want to talk about how to build your data foundations for AI, let’s connect.