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AI ethics & governance


The art of AI maturity: Advancing from practice to performance

Responsible AI: Scale AI with confidence

From AI compliance to competitive advantage

Explore organizations' attitudes towards AI regulation and their readiness to embrace it.

Benefits of Responsible AI

Minimize unintended bias

Build responsibility into your AI to ensure that the algorithms – and underlying data – are as unbiased and representative as possible.

Ensure AI transparency

To build trust among employees and customers, develop explainable AI that is transparent across processes and functions.

Create opportunities for employees

Empower individuals in your business to raise doubts or concerns with AI systems and effectively govern technology, without stifling innovation.

Protect the privacy and security of data

Leverage a privacy and security-first approach to ensure personal and/or sensitive data is never used unethically.

Benefit clients and markets

By creating an ethical underpinning for AI, you can mitigate risk and establish systems that benefit your shareholders, employees and society at large.

Responsible AI in HR

Enabling trustworthy AI

Principles and governance

Define and articulate a Responsible AI mission and principles, while establishing a transparent, governance structure across the organization that builds confidence and trust in AI technologies.

Risk, policy and control

Strengthen compliance with current laws and regulations while monitoring future ones, develop policies to mitigate risk and operationalize those policies through a risk management framework with regular reporting and monitoring. 

Technology and enablers

Develop tools and techniques to support principles such as fairness, explainability, robustness, traceability and privacy, and build them into the AI systems and platforms that are used.

Culture and training

Empower leadership to elevate Responsible AI as a critical business imperative and require training to provide all employees with a clear understanding of Responsible AI principles and criteria for success.

Identify AI bias before you scale

Case studies

Creating a sense of belonging

A global retailer and Accenture co-created a multiyear inclusion and diversity strategy to facilitate a greater sense of belonging for...

Evolving financial services

The Monetary Authority of Singapore and Accenture established the Veritas industry consortium to provide groundbreaking...

Fairness you can bank on

Applying algorithmic fairness to the real world of retail banking.


Our leaders

Ray Eitel-Porter

Managing Director – Data & AI, Global Lead for Responsible AI

Marisa Tricarico

Regional Lead – North America, Responsible AI

Rossana Bianchi

Regional Lead – Growth Markets, Responsible AI

Frequently asked questions