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Implementation

Responsible adoption of AI

Responsible adoption is not just about technology. It’s about leadership, governance, and a shared commitment to doing things right. We work closely with clients to navigate complexity and build solutions that are not only effective, but principled. 

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From readiness to responsibility

A framework for ethical and scalable AI

Adopting AI responsibly starts with understanding where you are and where you need to go. Twoday’s approach helps organizations move from exploration to execution.

01
Ethical design
Identifying risks early and embedding fairness, privacy, and societal impact into every solution.
02
Transparent operations
Ensuring stakeholders understand how AI systems work — supporting accountability and trust.
03
Governance and compliance
Aligning with regulatory standards and internal policies to ensure responsible deployment and lifecycle management.
04
Organizational readiness
Preparing teams, processes, and data foundations to support AI that delivers long-term value.
Responsible AI baseline

A starting point for principled innovation

Twoday’s Responsible AI Baseline is a practical foundation for organizations looking to adopt AI with confidence. It defines the minimum standards for responsible development and deployment helping teams align on what “good” looks like. 

The baseline includes: 

  • Clear principles for ethical AI design 
  • Guidelines for transparency and explainability 
  • Governance models for oversight and accountability 
  • Security and privacy protocols across the AI lifecycle 

This baseline is not a checkbox. It’s a mindset — embedded in how we build, collaborate, and deliver. 

Thomas Martinsen
Expertise that leads the way

AI is not just what we do. It’s who we are

Twoday’s strength lies in the depth of our expertise. Our AI specialists are not only highly skilled. They are deeply committed to responsible innovation. From data scientists and ML engineers to strategists and domain experts, our teams work across disciplines to ensure AI is operationalized with integrity. 

Experts like Thomas Martinsen and others help shape the future of AI across industries bringing clarity to complexity and turning strategy into measurable outcomes. 

We don’t just follow the best practices. We define them. 

Let's talk about responsible AI in your organization

Responsible AI engineering is a shared commitment across our teams — from data scientists and ML engineers to strategists and domain experts. It’s how we help clients lead with confidence, knowing their AI solutions are not only powerful, but principled.