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Responsible AI
When AI is trusted, it is used
Responsible AI creates the foundation for organizations to innovate, scale and realize value from AI with confidence. By embedding governance, transparency and oversight from the outset, AI becomes not only powerful, but trusted. Responsible AI helps organizations accelerate adoption, manage risk and move from experimentation to real business impact.
Governance
Establish the guardrails, oversight and accountability needed to scale AI responsibly.
Trust
Build transparent, fair and explainable AI systems that stakeholders can rely on.
Innovation
Accelerate AI adoption and unlock business value with confidence.
What is Responsible AI?
Responsible AI is the design, development, deployment and use of AI systems that prioritize ethical considerations while embedding governance and oversight. It ensures AI is transparent, fair and accountable throughout its lifecycle.
Done well, Responsible AI is not just about compliance. It enables organizations to scale AI with confidence, accelerate innovation and create sustainable business value while managing risk and maintaining trust.
Responsible AI vs. Ethical: what’s the difference?
Ethical AI focuses on the principles that guide what AI should and should not do. Responsible AI takes this a step further by putting those principles into practice through governance, oversight and risk management.
By embedding transparency, fairness and accountability into the AI lifecycle, Responsible AI helps organizations not only manage risk but also build trust, scale adoption and create long-term business value.
What are the nine principles of Responsible AI?
These principles provide a foundation for developing, deploying and scaling AI in a way that is trustworthy, transparent and aligned with business objectives.
Latest insights on Responsible AI
AI doesn't hallucinate, it optimizes for probability
AI doesn’t hallucinate, it predicts probabilities. Discover the risks, impacts and practical measures for responsible AI use.
AI Literacy: using AI responsibly across your organization
AI Literacy is critical for compliance and value creation under the EU AI Act. Discover the 5-step plan and get started today.
Responsible AI starts in the boardroom: here is how to make it scalable
Executives feel time pressure, but few leaders are ready for it. Control, governance, and skills determine who will truly move forward. Read the article!
A strong business case for Responsible AI: 10 success factors
Responsible AI is crucial for organizations that want to realize large-scale value without unacceptable risks. Read the article.
How can responsible AI bridge the gap between investment and impact?
Explore the ways in which responsible AI converts investment into meaningful impact.
How responsible AI can unlock your competitive edge
Discover how closing the AI confidence gap can boost adoption and create competitive edge. Explore three key actions for responsible AI leadership.
Seven guidelines for implementing Responsible AI
Explore EY's seven guidelines for implementing Responsible AI, ensuring ethics, transparency, and compliance while unlocking innovation and creating value.
EU AI Act Roadmap: What does the AI act mean for your organization?
The EU AI Act is coming soon. What does this mean and what steps should you take now?
How multidisciplinary collaboration on Responsible AI shapes a future with confidence
Discover insights from our EY AI Talks event on Responsible AI.
EY's commitment to developing and using AI ethically and responsibly
The EY organization is committed to the responsible and ethical design, implementation and use of AI systems. Learn more about our Responsible AI principles.
Frequently Asked Questions about Responsible AI
Experience in our Responsible AI Workshop how ethical, compliant AI drives value while managing risk.
Are you ready for the EU AI Act?
The EU AI Act is now in effect, putting the EU at the forefront of AI regulation and innovation. It aims to unify rules for AI development, market placement, and usage while addressing risks through a risk classification system. Organizations using AI must comply with mandatory requirements for risk management, data governance, and human oversight.
For more information, download the key highlights of the EU AI Act.
Key highlights of the EU AI Act summarized
How EY can help
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Comply with the EU AI Act. EY's EU AI Act Maturity Assessment helps evaluate AI systems and implement Responsible AI practices.
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We can help you drive confidence in data, technology and processes that form the infrastructure of your AI ecosystem. Learn more..
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Experience AI innovation at the EY.ai Lab! Collaborate with multidisciplinary teams to develop tailored solutions that address your unique business needs.
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Through careful analysis of emerging signals and trends, EY has identified four distinct scenarios for how AI could reshape the business landscape by 2030.
Read more
How EY ensures compliance in its own AI journey
How EY is navigating global AI compliance: The EU AI Act and beyond
Read case studyBy embedding ethical principles, promoting cross-functional collaboration, and staying engaged with regulators, EY's approach to AI governance has not only positioned the organization to meet regulatory requirements but also to transform AI into a strategic asset.
How an AI‑driven transformation helped a global brewer accelerate growth
Asahi E&I partnered with EY and Microsoft to transform trade promotion optimization.
Read case studyTechnology is advancing at an unprecedented pace. It requires you to rethink how your organization is structured. By continuously collaborating with EY and other ecosystem partners, we’re able to keep evolving our business.
Case study: Life sciences
How a global biopharma became a leader in ethical AI
Read case studyEY teams could work with us on how a Responsible AI assessment should look, meshing what we were doing with their global Responsible AI framework and working their magic to join the dots.
How is FrieslandCampina transforming into a data-centric organization?
How FrieslandCampina’s data platform paves the way for AI innovation
Read moreThe combination of Power BI and Databricks enables everyone—from analyst to engineer—to work from a single platform towards better decisions
Discover the story behind EY's EYQ
How EY is unlocking the next iteration of GenAI advancement with EYQ
Read moreStrategic foresight and responsiveness are crucial in leveraging emerging technologies like GenAI to drive organizational transformation. Understanding and addressing the unique challenges of GenAI allows us to harness its potential responsibly and effectively.
The EY ‘Client Zero’ Story
How EY navigated its own AI-driven transformation
Read moreBy acting as our own ‘Client Zero’, EY is determining answers to these questions now – so that we can guide our clients based on real experience and practical use cases of AI technology.
Case study: Employee productivity
How GenAI is empowering talent at a PE-backed consumer brand
Read case studyThe EY team provided a clear framework that was critical to help us navigate how to deploy AI to empower our people, taking both a practical and inspirational approach
Case study: Data automation
How a Nordic insurance company automated claims processing
Read case studyOur team provided a solution that did more than just digitize and organize unstructured data. It combined EY business insights and industry knowledge within a strategic technology ecosystem to help modernize the insurer's operations.
Case study: Vendor management
How AI helped a major IT company to improve its vendor interaction experience
Read case studyWe help businesses build their own automation capabilities to improve governance, reduce costs and help create long-term value. EY Fabric AI Space helped our client resolve vendor queries nonstop, resulting in a manual effort reduction and enhanced vendor experience.
Case study: Banking
Using AI to improve a bank’s agent effectiveness
Read case studyBy addressing the quality issues inherent in conversations recorded by legacy systems and over-reliance on keywords, we were able to identify very subtle signals with a very high level of accuracy.
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