What Good Looks Like in AI Customer Service And Why It Matters
- Nick O'Halloran
- 1 day ago
- 2 min read
There is a growing gap in the market between AI that works and AI that is ready for real world deployment.
The difference is not performance.
It is trust, governance, and operational maturity.
Before deploying AI into customer facing environments, businesses should be measuring against a clear definition of what good looks like:
Privacy by design, embedded into the architecture
Clear and enforceable data governance
Transparency with customers at every interaction
Full auditability across all conversations and actions
Enterprise level security as a baseline
These are not optional extras. They are the foundation.
The Reality: Most AI Does Not Meet This Standard
Many new entrants in the AI space focus on speed to market and price.
But in industries like automotive and enterprise customer service, the risks are materially higher.
Personally identifiable information is exchanged daily
Financial and compliance exposure is real
Customer trust directly impacts revenue and retention
A lower cost solution that lacks governance, auditability, or security does not reduce cost. It shifts risk.
What This Looks Like in Practice
At Contact Harald, this framework has been built into the core of Ask Harry from day one.
This is not new territory.
With over 14 years of experience in technology, we have operated in environments where data sensitivity, compliance, and system reliability are non negotiable. That experience directly informs how Ask Harry is designed and deployed.
Where Ask Harry Meets the Standard
Privacy by design is embedded at the architectural level, not layered on later.
Clear data governance ensures full visibility of how data is captured, stored, and accessed.
Transparency with customers is built into every interaction, so customers understand when they are engaging with AI and how their information is handled.
Full auditability means every interaction is traceable, supporting compliance, accountability, and continuous improvement.
Enterprise level security underpins the entire platform, with strong frameworks, encryption, and ongoing monitoring in place.
Built with Legal and Security at the Core
A key differentiator is the involvement of in-house legal counsel in shaping the product.
This ensures alignment with Australian privacy requirements, clear frameworks for data handling, and reduced risk exposure for every business deploying the technology.
As Kate Pullinger, in house legal counsel, notes:
“Security and privacy cannot be treated as add-ons in AI. They must be designed into the system from the outset, with clear accountability, transparency, and control over how data is handled at every stage.”
Security is not treated as a feature. It is part of the foundation.
The Bottom Line
AI is moving quickly into customer service environments.
But capability alone is not enough. Without strong security, governance, and accountability, AI introduces risk rather than removing it.
Ask Harry has been built to meet the standard that real businesses require. Not just to function, but to operate securely, transparently, and at scale.
That is what good looks like.
