Information Governance in the age of AI

Blogs and Articles

As it integrates into the global economy, artificial intelligence (AI) is having a profound impact on Information and Data Governance. Every day, the landscape evolves. The latest Iron Mountain Education Series discussion explores the implications of AI on the economy, regulatory structures, and data management.

Sue Trombley
Sue Trombley
May 7, 20247 mins
Information Governance in the age of AI

Iron Mountain’s 2024 Education Series continued with one of the most talked about topics of the past year: AI. Since airing a similar discussion in July 2023, we’ve seen AI rapidly expand its influence on the global economy—and Information Governance in particular. 

In Information Governance in the age of AI, we welcomed two pioneering experts in this exciting and potentially risky new frontier, Kelly McIsaac, Associate Vice President, Data Risk Policies and Standards at TD Bank, and Brian O’Flynn, Director of Digital Marketing at Iron Mountain. This critical conversation on the advancements, challenges, and opportunities in Information and Data Governance will surely expand your insight, regardless of where your organization is with AI adoption. 

We polled more than 500 webinar attendees to see if their organization currently has AI usage policies. Stunningly—given the attention to risks related to AI—over half of respondents have not been provided guidance by their organizations:

Information Governance in the age of AI - Results of the poll posing the question whether the organization of working at is using AI policies or not

43% answered Yes; 57% answered No or Unsure


Join the conversation: Does your
organization have AI usage policies in place?

Share your insights

The expanding influence of AI on Information Governance

The rise and swift integration of AI has brought new concerns related to risk management across the globe. Central to these concerns is Information Governance, which plays a pivotal role in understanding and managing the risks associated with AI technologies and their impact on information, data, and records. All of which necessitate clear policies for usage.

Video clip: Trends in the rise of AI in large organizations

The rapid advancement in, and adoption of, AI technologies poses specific challenges in information security, intellectual property, and regulatory restrictions. New fiscal opportunities are emerging as content providers partner with major tech companies to train AI models. The growing AI data market anticipates a valuation of $30 billion in the coming years. There’s no question that AI is pushing the limits of how we define and balance information security and financial opportunity.

It’s time to explore whether these theories and experiments, when applied practically, can create value. What are the emergent opportunities and challenges?
Brian O’FlynnDirector of Digital Marketing, Iron Mountain

Navigating the regulatory landscape

As AI integrates rapidly into the global economy, the urgency to regulate the AI space intensifies. Vigilance around cybersecurity, copyright law, and the potential for political and media manipulation with deep fakes continues to be front and center for today’s policymakers. Governments worldwide are stepping in to address the risks associated with AI models and their implications on society. The European Union’s AI Act is a prominent example of such intervention, highlighting a significant shift toward model risk management and third-party risk scrutiny. 

Both policymakers and organizations must work collaboratively to establish robust governance structures that can adapt to the rapid pace of AI development while safeguarding public interest and trust.
Kelly McIsaacAssociate Vice President, Data Risk Policies and Standards, TD Bank

Organizations, likewise, are slowly beginning to establish usage policies, codes of practice, and centers of excellence as evidenced by our polling question results. This trend is fueled by the need to ensure that AI systems are safe, compliant, and ethical and align with the organization’s broader Information Governance policies. The challenges presented by the use of AI require a holistic approach to governance. The focus on regulating AI should not only protect customers but also establish a foundation of trust in AI technologies themselves, and the data used for modeling, which is essential for their successful integration.

Video clip: Where is AI increasing the risk in Data Governance?


Related: Eyes on Data: Importance of
Data Governance when implementing AI/ML

Learn more

The trustworthiness of data is a key concern in the growing use of AI

One thing that AI hasn’t changed this year? The need for data integrity. As they have always done, organizations must use trusted data sources to preserve the validity, transparency, and accuracy of their technology-driven data outcomes. “Any risks we were concerned about before with data are just becoming exponentially bigger,” says McIssac.

Understanding data lineage and managing your organization’s data hygiene and data supply chain have always been important, but now they are critical in establishing trust in AI-driven output. According to a recent survey from Salesforce, nearly 70% of workers who don’t trust the data that trains AI are hesitant to adopt it. Privacy, compliance, transparency, and vigilance against AI bias are imperative for building and ensuring this trust.

Strong delivery of services to build trust and value with your customers is based on truly knowing your data and knowing that your data is being used for the right purpose. Organizations need to certify their data sources to prove the lineage appropriately and indicate controls along the path.
Kelly McIsaacAssociate Vice President, Data Risk Policies and Standards, TD Bank

In the age of AI, it’s more important than ever to integrate your organization’s data supply chain within organizational controls and governance frameworks. How are your vendors using AI? Where do your AI models source their data sets? This governance of data is at the heart of AI adoption and its implications for the future.

Video clip: Building trust in data for successful AI strategy

secure cloud

Related: How to safeguard your data
in the fast-moving world of generative AI

Learn more

What’s next for Information Governance in the age of AI?

As AI continues its rapid integration into various industries, a significant focus is placed on governance and risk management. The role of Information Governance is critical in upholding standards, contributing to AI governance, and ensuring the trustworthiness of AI applications now and in the future.

The development of new roles such as Chief AI Officer, along with the establishment of AI centers of excellence, are integral parts of many organizations’ AI strategies. Making connections between Information Governance and others in your organization who seek the secure and effective adoption of AI will open doors for further opportunity.

Be calm, be methodical. The tenets of governance, information management, security, compliance, and the fundamentals are still valid. We will learn how to best apply them in the new wave of AI.
Brian O’FlynnDirector of Digital Marketing, Iron Mountain

Watch the full webinar

Interested in learning more about this topic? Visit Iron Mountain’s 2024 Education Series to watch the on-demand recording of Information Governance in the age of AI and to register for upcoming webinars.

Information Governance in the age of AI

We’ve got the highlights from our expert panel Kelly McIsaac and Brian O’Flynn on:

  • The expanding influence and risk of AI 
  • The trustworthiness of data as a key concern with AI
  • The evolving role of information and data governance

Watch now on-demand