Privacy goes beyond compliance.
Contribution by Orla Dijkink – Lead OutSystems at LINKIT
Digital agents process information, make decisions, and learn from data. Without clarity about how that data is used, doubt quickly arises—among customers, employees, and regulators alike.
Organisations that put transparency at the core, however, build trust. They demonstrate that AI is not something that operates “in the dark,” but a tool that is explainable, controllable, and accountable.
Insight into what an agent does
An AI agent that uses data must be able to explain why. Within the OutSystems AI Workbench, that visibility is built in by default:
- You can see which data is being used
- How decisions are made
- And which steps the agent has taken to reach a result
This is not only essential for compliance but also for internal AI adoption. Employees are more willing to trust the output of an agent when they understand how decisions are made. This level of explainability and traceability aligns with guidelines from OWASP and Google Cloud AI Governance, which emphasise responsible AI usage.
Privacy as a strategic advantage
Transparency delivers more than regulatory compliance. It strengthens relationships with customers and users, improves data quality, and drives more consistent decision-making.
The Workbench supports full traceability of decisions, including logs and audit trails per agent. This enables organisations to comply with emerging AI regulations, such as the EU AI Act, while building internal confidence in AI-driven processes.
Organisations that treat privacy and transparency as foundational principles also benefit from faster adoption. Users no longer see AI as a threat, but as an enhancement to their work.
Why this matters now
More and more processes are being supported by agentic AI.
According to Gartner, by 2028, one-third of all enterprise software will include agentic capabilities, and up to 20% of digital customer interactions will be handled by AI agents.
By investing now in explainability, governance, and responsible data usage, you prevent future complexity and reputational risks. You create an AI environment where every decision can be justified, and where humans and machines reinforce each other.
