Responsible by Design: Our Methodology

Responsible by Design Methodology

We embed our principles into every stage of the development lifecycle, not just at the end. This is what "Responsible-by-Design" means in practice. Every in-platform AI capability at impact.com moves through these six phases.

1

Requirements

• Governance & risk review: a pre-spec review with senior stakeholders before resources are committed.
• Technological intentionality: we ask, "Is AI the right tool for this problem?" and only commit to AI when its benefits demonstrably outweigh the risks.
• Centralized oversight: all AI projects are tracked in a single space for full visibility across the company.

2

Design

• AI identification: clearly label every AI interaction for the user.
• User control & feedback: opt-outs, settings, and feedback channels built in.
• Inclusive & accessible design: features usable by everyone, including people who rely on assistive technologies.
• Privacy-by-design architecture: data minimization and robust authorization built into the foundation.

3

Implementation

• Robust audit trails: log significant AI actions on a per-user basis for accountability.
• Secure coding: protect the system and its data from vulnerabilities.

4

Testing

• Intensive security testing: vetted internally and by external white-hat experts.
• Fairness & bias audits: check for performance disparities and apply safety tooling (such as Google's Model Armor).

5

Deployment

• Transparent documentation: model cards, help articles, and specs for different audiences.
• Continuous monitoring: track performance and drift, with humans in the loop.

6

Maintenance & continuous improvement

• Iterative feedback loops: feedback from monitoring, real user interactions, and testing flows back into the lifecycle.
• A learning culture: an active internal AI community shares knowledge and challenges our assumptions, so we keep improving and stay ahead of emerging risks.