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Accelerate innovation and strengthen trust in AI solutions
Responsible AI
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 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 build trust with AI initiatives.
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.
Companies are increasingly faced with tough questions:
Are your AI initiatives proceeding at the pace you need them to — or are they falling behind your ambition?
What measurable value are you getting from your AI investments — and how are you tracking it across your business?
Is your AI strategy fully aligned with your broader business objectives and long-term vision?
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 confidently explain and document how your AI governance, risk management and compliance processes work?
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 — so you can accelerate innovation while building trust and preserving value.
- Assess your baseline
- Foundational capabilities
- Operating model and governance design
- Application lifecycle
- Beyond initial steps
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 expand their AI initiatives, risk management functions should scale and evolve to keep pace. To operationalize Responsible AI effectively, these key functions will be essential:
Internal audit
Cybersecurity
Data governance
Compliance and legal
Regulatory readiness
Data risk and privacy
Responsible AI in action
At PwC, we’re our own case study — transforming our own business, at scale, across all our functions to better understand how to serve our clients. We are taking advantage of the transformational nature of AI to achieve more by putting the technology directly in the hands of our people and our clients. Our goal is to integrate AI into our capabilities and tools to drive tangible, practical benefits — while confirming its responsible use. Interested in learning the benefits? Contact us today.
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Contact us
Jennifer Kosar
AI Assurance Leader, PwC US
Rohan Sen
Principal, Data Risk and Responsible AI, PwC US
US Private Practice Leader, New York, PwC US
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