Responsible AI

Practices to accelerate innovation and build trust in AI solutions

In a world where the pace of innovation is measured in days and weeks rather than months and years, and where breakthroughs in technology are announced with increasing frequency, it’s necessary to foster rapid progress in your AI strategy while effectively preserving value, delivering ROI and managing risks.

When confronted with novel technologies (and therefore potentially novel risks), the typical instinct is to be conservative. But conservatism is not an option when the world is moving fast.

Responsible AI is a set of practices that help create confidence in decisions, balancing the risks and rewards of adopting AI technologies and solutions. Responsible AI helps AI initiatives succeed more quickly, often with fewer issues, pauses and mistakes.

Risk is more effectively managed through standardized measurement and evaluation of risks, governance and controls commensurate with the risks, and tools to monitor performance over time.

Where are you on your Responsible AI journey?

Curious to know where your organization stands relative to your peers in areas of Responsible AI? Take our Responsible AI survey and receive an immediate benchmark report with actionable insights.

Companies are increasingly faced with tough questions:

  • Are your AI initiatives proceeding at the pace you need them to?
  • What value are you receiving from your AI investments?
  • Is your AI strategy aligned with your overall business strategy?
  • How do your AI applications reflect your company’s policies and values?
  • How do you manage risks associated with the adoption and use of AI?
  • Can you provide documented evidence that you are operating in compliance with regulations to your stakeholders?
  • Do you feel confident in your third-party AI tools?
  • Are you respecting your customers’ and other stakeholders’ privacy rights?

Your answers should start and end with Responsible AI.

How PwC can help

We help our clients build AI programs designed to efficiently assess and address risks, proactively respond to AI requirements and develop and implement sustainable processes – all of which can help accelerate innovation while building trust and preserving value.

Assess your baseline

Evaluate whether your current processes, policies, and operating model reflect Responsible AI leading practices and align with your organization’s AI ambitions.

Foundational capabilities

Set the foundation for your program with the following foundational capabilities:

  • Responsible AI principles
  • AI use case inventory
  • AI risk taxonomy
  • AI risk intake and tiering

Operating model and governance design

Operationalize foundational capabilities through an accountability – and communication – structure that will set your organization up for success:

  • Operating model – roles and responsibilities
  • Governance committee and escalations
  • AI risk and control matrix
  • Training and communication

Application lifecycle

Establish processes, standards and testing to build perpetual trust and transparency in your implementations:

  • AI development and deployment standards
  • AI testing and monitoring (including model testing, red teaming)
  • Risk mitigation tracking and reporting

Beyond initial steps

Responsible AI is a journey. As organizations continue to drive AI initiatives and the footprint of AI within organizations continues to grow, various risk management functions will need to scale and evolve to meet the needs of AI. Here are some functions that will be critical in operationalizing Responsible AI:

  • Internal audit
  • Cybersecurity
  • Data governance
  • Compliance and legal
  • Regulatory readiness
  • Data risk and privacy

Responsible AI in action: Client zero

At PwC, we are client zero and transforming our own business, at scale, across all of our functions to better understand how to serve our clients. Responsible AI is human-led and tech-powered, and we are taking advantage of the transformational nature of GenAI and putting the technology directly in the hands of our people and our clients. Our goal is to embed AI into our capabilities and tools used across our business to deliver tangible, practical benefits, while using the technology in a responsible way. Interested in learning the benefits? Contact us today.

Contact us

Jennifer Kosar

AI Assurance Leader, PwC US

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Rohan Sen

Principal, Data Risk and Responsible AI, PwC US

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Shawn Panson

US Private Practice Leader, New York, PwC US

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