Why now is the time for AI governance

Thought leadership

AI is here and its potential is enormous. But data professionals know that managing an AI roadmap can be challenging, especially if your organization lacks trusted data. Without trusted data, you can’t build trusted AI. In our era of AI-driven transformation, forward-thinking organizations integrating AI into the roadmap know that AI governance can make all the difference. 

Recently, AI experts from Collibra and Deloitte teamed up to discuss trusted AI and how organizations can use a trusted AI framework to get the most out of AI data governance.

Watch the webinar: Six pillars of Trustworthy AI™ and the data that drives it

The AI era is here

As AI technologies become more sophisticated and widespread, the potential for unintended consequences, ethical dilemmas and compliance challenges also rises. 

Trusted AI is about building AI systems that are not only technically sound but also socially responsible, addressing concerns like data privacy, bias, transparency, and accountability.

“There are huge data sets used to frame these AI models to come up with these responses. The data itself, the algorithms that go into it, and the calculations that happen are really, really complex. It’s essential that we understand and appreciate the complexity.” 

– Simla Sivanandan, Senior Manager, Data Intelligence at Collibra

The need for trusted AI

The journey towards realizing the full benefits of AI starts with establishing trust — both in the AI systems themselves and in the data that powers them. 

Trustworthy AI is not just about technology; it’s also about the governance, ethical considerations, and compliance standards that guide AI development and deployment.

In this webinar, AI experts from Deloitte and Collibra explore key aspects of trusted AI, including:

  • Ethical AI practices: Addressing the moral implications of AI, ensuring that AI systems are fair, transparent, and accountable.
  • Data governance and quality: Ensuring the integrity, accuracy, and reliability of the data feeding into AI systems.
  • Compliance and regulatory adherence: Navigating the complex landscape of laws and regulations that govern AI usage across different industries and regions.
  • Risk management: Identifying and mitigating the potential risks associated with AI, including biases, privacy breaches, and security vulnerabilities.
  • Stakeholder engagement and transparency: Engaging stakeholders effectively and maintaining transparency throughout the AI lifecycle.
  • Operationalizing AI governance: Implementing practical steps and processes to embed AI governance into the fabric of the organization.

Plus, you’ll see a demo of the Deloitte trusted AI impact assessment tool — a powerful solution for identifying ethical considerations across the model development process.

Are you on your organization’s AI journey without AI governance? 

Watch the webinar: Six pillars of Trustworthy AI™ and the data that drives it 

You’ll get insights and practical advice on how to develop and manage AI applications responsibly, ensuring they deliver value ethically and sustainably. You’ll gain a deeper understanding of how to build and maintain trust in your AI initiatives, and you’ll discover how to turn the challenges of AI into opportunities by embracing a comprehensive framework for trusted AI.

Learn more about Collibra AI Governance.

Related resources

Education

Learn more about AI governance

Blog

Building your enterprise AI governance roadmap in our AI-powered world

Blog

Key AI governance principles for enterprises

View all resources

More stories like this one

Nov 6, 2024 - 4 min read

AI and data compliance: How the AI Act will impact your organization

Read more
Arrow
Aug 28, 2024 - 4 min read

AI governance versus model management: What’s the difference?

Read more
Arrow
Aug 19, 2024 - 4 min read

Understanding the importance of data governance in the age of AI

Read more
Arrow