Blog Post

AI Governance: The Relyance AI Approach

In the wake of the EU AI Act's passage and amidst the burgeoning AI revolution, organizations worldwide are grappling with how to harness AI's potential ethically and responsibly. Relyance AI stands at the vanguard, ready to demystify AI governance with its innovative approach. This blog reveals how Relyance AI, leveraging its cutting-edge code scanning techniques and NLP models, provides a comprehensive framework for identifying AI systems, assessing risks, and ensuring compliance.

March 19 2024

The recent approval and passage of the EU AI Act has been monumental - and rightfully so - has raised many questions among various stakeholders. This recent approval comes on the heels of an astronomical explosion in the use of AI tools, models, and generative AI systems across the board. AI has been, and is poised to, increasingly continue as one of the most significant technology developments of our lifetimes (on par with the internet) and undoubtedly has everyone thinking about leveraging it. Organizations across every industry sector are beginning to approach this situation and figure out appropriate ways to incorporate AI in ways that respect their customers.

At Relyance AI, we are intimately familiar with AI and have heard a stream of questions from the broader community:

“I am not sure what my next steps should be. It’s overwhelming.”

“How will I keep up with the changing AI landscape when new models and capabilities are introduced daily?”

“Who should own AI governance in my company? Should it be the privacy team? Or the security team? Or both?”

We get it. It’s the wild west out there, but know you are not alone.

The Basics

There is a lot of content on AI Governance, but in simple terms, AI Governance includes the following steps. First, identify AI systems and models used by your application(s), the third parties in use, and the types of data flows that feed in and out of those. Second, gather visibility into the associated metadata around these systems to help you understand their risk and compliance profile, and clearly understand your compliance obligations. And third, take action on this information. At Relyance AI, we believe that AI governance and risk in the context of data protection are shared responsibilities between privacy, security, and governance teams, and collaboration is embedded into our platform to streamline that process for users.

For Privacy teams, in addition to the EU AI Act, the NIST Risk Management Framework, the recent Executive Order on AI, and other regulations like the Canadian Artificial Intelligence and Data Act, regulators across the U.S. (at the federal and the state level) and across the globe have been prolific in introducing legislation and being active to address artificial intelligence. It is clear that understanding AI systems, conducting assessments, understanding the data they process, and the risk they pose based on different controls from various regulations, as well as using this information to create transparency for end users, will be crucial.

For Security Teams, AI governance requires getting visibility into data flows and establishing policies, procedures, and controls to ensure that AI systems don’t introduce mission-critical vulnerabilities and are transparent, unbiased, and accountable. By integrating AI Governance into cybersecurity processes and practices, organizations can enhance their security posture by developing and deploying AI systems responsibly, thereby mitigating potential harm to their organization and customers. AI systems can bring in a host of new threats like data poisoning, model theft, model evasion, and more. It will be critical for security teams to gain visibility and prepare defenses for these new attack vectors.

Regardless of your role within the organization, effective AI governance can only begin if you know what your AI landscape looks like and when it changes. From there, different governance layers and policies can be applied to comply with regulations, mitigate risks, and, most importantly, keep your customer's data safe.

Why is Relyance AI uniquely positioned to solve this problem?

At Relyance AI, our fundamental ethos from the company's inception has been “Privacy. It’s in the Code.” Relyance AI has been at the forefront of using patented intelligent code scanning techniques and triangulating that with specialized integrations to understand the data landscape, make sense of it from a compliance and a risk lens, and build more robust data protection programs. Our architecture and approach prime us to help our users solve AI governance as the next natural step. By using our best-in-class code scanning techniques, our integration capabilities, and our state-of-the-art NLP models for scanning contractual obligations, Relyance AI can help customers with:

  • Identifying and cataloging your AI systems and models: Relyance AI can determine which AI systems and underlying models are being used, where they live in your organization, what type of data is being fed into these systems and models, and any other associated metadata. We firmly believe that governance will be futile unless organizations solve this fundamental discovery piece at scale.
  • Identify compliance obligations and conduct assessments: Relyance AI can help you conduct AI risk assessments and identify compliance obligations based on the risk categorization of AI systems. Using our best-in-class NLP capabilities and homegrown models, we can enable you to review agreements and policies on a large scale, understand AI system usage, and track the safeguards put in place by your third-party systems.
  • Identify and resolve vulnerabilities that pose a risk: AI systems and models pose a massive security risk for most companies. These new attack vectors not only increase in your own application and product development areas that use AI, but they also increase in your supply chain. Your vendors are introducing AI capabilities to create value, increasing attack vectors for your organization. By helping create visibility around potential threats and data flows from your application's AI systems and those of your third-party vendors, we arm security teams with all the information they need to keep their crown jewels secure.
  • Continuous monitoring: Relyance AI is built with a continuous monitoring lens, and we will use the same philosophy and architecture to help you govern AI systems. Governance will only be effective if you match it with the speed of technology development and have a system in place that continuously monitors, updates, and proactively alerts throughout your AI landscape.
  • Building policies and controls: With the explosion in different rules and regulations around AI (like the EU AI Act, the Canadian AIDA, the NIST AI framework, or state-specific regulations like in New York or Colorado, to name a new), we recognize that every organization will interpret these differently in the unique context of their organization. Relyance AI can enable you with out-of-the-box policies and provide you the flexibility to define your own rules and policies to stay ahead of various compliance regulations

We look forward to embarking on this journey with you. Our ethos at Relyance AI has always been to advance technology to build best-in-class data protection programs. We are privileged and enthusiastic to be in this position to help our customers address the explosion in AI systems, the associated security complications, and the increasing regulation that comes with them. We’re committed to helping organizations navigate this new era and usher in the age of AI.

What’s a Rich Text element?

The rich text element allows you to create and format headings, paragraphs, blockquotes, images, and video all in one place instead of having to add and format them individually. Just double-click and easily create content.

Title

Static and dynamic content editing

A rich text element can be used with static or dynamic content. For static content, just drop it into any page and begin editing. For dynamic content, add a rich text field to any collection and then connect a rich text element to that field in the settings panel. Voila!

How to customize formatting for each rich text

Headings, paragraphs, blockquotes, figures, images, and figure captions can all be styled after a class is added to the rich text element using the "When inside of" nested selector system.

Blog Post

AI Governance: The Relyance AI Approach

In the wake of the EU AI Act's passage and amidst the burgeoning AI revolution, organizations worldwide are grappling with how to harness AI's potential ethically and responsibly. Relyance AI stands at the vanguard, ready to demystify AI governance with its innovative approach. This blog reveals how Relyance AI, leveraging its cutting-edge code scanning techniques and NLP models, provides a comprehensive framework for identifying AI systems, assessing risks, and ensuring compliance.

March 19 2024

The recent approval and passage of the EU AI Act has been monumental - and rightfully so - has raised many questions among various stakeholders. This recent approval comes on the heels of an astronomical explosion in the use of AI tools, models, and generative AI systems across the board. AI has been, and is poised to, increasingly continue as one of the most significant technology developments of our lifetimes (on par with the internet) and undoubtedly has everyone thinking about leveraging it. Organizations across every industry sector are beginning to approach this situation and figure out appropriate ways to incorporate AI in ways that respect their customers.

At Relyance AI, we are intimately familiar with AI and have heard a stream of questions from the broader community:

“I am not sure what my next steps should be. It’s overwhelming.”

“How will I keep up with the changing AI landscape when new models and capabilities are introduced daily?”

“Who should own AI governance in my company? Should it be the privacy team? Or the security team? Or both?”

We get it. It’s the wild west out there, but know you are not alone.

The Basics

There is a lot of content on AI Governance, but in simple terms, AI Governance includes the following steps. First, identify AI systems and models used by your application(s), the third parties in use, and the types of data flows that feed in and out of those. Second, gather visibility into the associated metadata around these systems to help you understand their risk and compliance profile, and clearly understand your compliance obligations. And third, take action on this information. At Relyance AI, we believe that AI governance and risk in the context of data protection are shared responsibilities between privacy, security, and governance teams, and collaboration is embedded into our platform to streamline that process for users.

For Privacy teams, in addition to the EU AI Act, the NIST Risk Management Framework, the recent Executive Order on AI, and other regulations like the Canadian Artificial Intelligence and Data Act, regulators across the U.S. (at the federal and the state level) and across the globe have been prolific in introducing legislation and being active to address artificial intelligence. It is clear that understanding AI systems, conducting assessments, understanding the data they process, and the risk they pose based on different controls from various regulations, as well as using this information to create transparency for end users, will be crucial.

For Security Teams, AI governance requires getting visibility into data flows and establishing policies, procedures, and controls to ensure that AI systems don’t introduce mission-critical vulnerabilities and are transparent, unbiased, and accountable. By integrating AI Governance into cybersecurity processes and practices, organizations can enhance their security posture by developing and deploying AI systems responsibly, thereby mitigating potential harm to their organization and customers. AI systems can bring in a host of new threats like data poisoning, model theft, model evasion, and more. It will be critical for security teams to gain visibility and prepare defenses for these new attack vectors.

Regardless of your role within the organization, effective AI governance can only begin if you know what your AI landscape looks like and when it changes. From there, different governance layers and policies can be applied to comply with regulations, mitigate risks, and, most importantly, keep your customer's data safe.

Why is Relyance AI uniquely positioned to solve this problem?

At Relyance AI, our fundamental ethos from the company's inception has been “Privacy. It’s in the Code.” Relyance AI has been at the forefront of using patented intelligent code scanning techniques and triangulating that with specialized integrations to understand the data landscape, make sense of it from a compliance and a risk lens, and build more robust data protection programs. Our architecture and approach prime us to help our users solve AI governance as the next natural step. By using our best-in-class code scanning techniques, our integration capabilities, and our state-of-the-art NLP models for scanning contractual obligations, Relyance AI can help customers with:

  • Identifying and cataloging your AI systems and models: Relyance AI can determine which AI systems and underlying models are being used, where they live in your organization, what type of data is being fed into these systems and models, and any other associated metadata. We firmly believe that governance will be futile unless organizations solve this fundamental discovery piece at scale.
  • Identify compliance obligations and conduct assessments: Relyance AI can help you conduct AI risk assessments and identify compliance obligations based on the risk categorization of AI systems. Using our best-in-class NLP capabilities and homegrown models, we can enable you to review agreements and policies on a large scale, understand AI system usage, and track the safeguards put in place by your third-party systems.
  • Identify and resolve vulnerabilities that pose a risk: AI systems and models pose a massive security risk for most companies. These new attack vectors not only increase in your own application and product development areas that use AI, but they also increase in your supply chain. Your vendors are introducing AI capabilities to create value, increasing attack vectors for your organization. By helping create visibility around potential threats and data flows from your application's AI systems and those of your third-party vendors, we arm security teams with all the information they need to keep their crown jewels secure.
  • Continuous monitoring: Relyance AI is built with a continuous monitoring lens, and we will use the same philosophy and architecture to help you govern AI systems. Governance will only be effective if you match it with the speed of technology development and have a system in place that continuously monitors, updates, and proactively alerts throughout your AI landscape.
  • Building policies and controls: With the explosion in different rules and regulations around AI (like the EU AI Act, the Canadian AIDA, the NIST AI framework, or state-specific regulations like in New York or Colorado, to name a new), we recognize that every organization will interpret these differently in the unique context of their organization. Relyance AI can enable you with out-of-the-box policies and provide you the flexibility to define your own rules and policies to stay ahead of various compliance regulations

We look forward to embarking on this journey with you. Our ethos at Relyance AI has always been to advance technology to build best-in-class data protection programs. We are privileged and enthusiastic to be in this position to help our customers address the explosion in AI systems, the associated security complications, and the increasing regulation that comes with them. We’re committed to helping organizations navigate this new era and usher in the age of AI.

What’s a Rich Text element?

The rich text element allows you to create and format headings, paragraphs, blockquotes, images, and video all in one place instead of having to add and format them individually. Just double-click and easily create content.

Title

Static and dynamic content editing

A rich text element can be used with static or dynamic content. For static content, just drop it into any page and begin editing. For dynamic content, add a rich text field to any collection and then connect a rich text element to that field in the settings panel. Voila!

How to customize formatting for each rich text

Headings, paragraphs, blockquotes, figures, images, and figure captions can all be styled after a class is added to the rich text element using the "When inside of" nested selector system.

AI Governance: The Relyance AI Approach

The recent approval and passage of the EU AI Act has been monumental - and rightfully so - has raised many questions among various stakeholders. This recent approval comes on the heels of an astronomical explosion in the use of AI tools, models, and generative AI systems across the board. AI has been, and is poised to, increasingly continue as one of the most significant technology developments of our lifetimes (on par with the internet) and undoubtedly has everyone thinking about leveraging it. Organizations across every industry sector are beginning to approach this situation and figure out appropriate ways to incorporate AI in ways that respect their customers.

At Relyance AI, we are intimately familiar with AI and have heard a stream of questions from the broader community:

“I am not sure what my next steps should be. It’s overwhelming.”

“How will I keep up with the changing AI landscape when new models and capabilities are introduced daily?”

“Who should own AI governance in my company? Should it be the privacy team? Or the security team? Or both?”

We get it. It’s the wild west out there, but know you are not alone.

The Basics

There is a lot of content on AI Governance, but in simple terms, AI Governance includes the following steps. First, identify AI systems and models used by your application(s), the third parties in use, and the types of data flows that feed in and out of those. Second, gather visibility into the associated metadata around these systems to help you understand their risk and compliance profile, and clearly understand your compliance obligations. And third, take action on this information. At Relyance AI, we believe that AI governance and risk in the context of data protection are shared responsibilities between privacy, security, and governance teams, and collaboration is embedded into our platform to streamline that process for users.

For Privacy teams, in addition to the EU AI Act, the NIST Risk Management Framework, the recent Executive Order on AI, and other regulations like the Canadian Artificial Intelligence and Data Act, regulators across the U.S. (at the federal and the state level) and across the globe have been prolific in introducing legislation and being active to address artificial intelligence. It is clear that understanding AI systems, conducting assessments, understanding the data they process, and the risk they pose based on different controls from various regulations, as well as using this information to create transparency for end users, will be crucial.

For Security Teams, AI governance requires getting visibility into data flows and establishing policies, procedures, and controls to ensure that AI systems don’t introduce mission-critical vulnerabilities and are transparent, unbiased, and accountable. By integrating AI Governance into cybersecurity processes and practices, organizations can enhance their security posture by developing and deploying AI systems responsibly, thereby mitigating potential harm to their organization and customers. AI systems can bring in a host of new threats like data poisoning, model theft, model evasion, and more. It will be critical for security teams to gain visibility and prepare defenses for these new attack vectors.

Regardless of your role within the organization, effective AI governance can only begin if you know what your AI landscape looks like and when it changes. From there, different governance layers and policies can be applied to comply with regulations, mitigate risks, and, most importantly, keep your customer's data safe.

Why is Relyance AI uniquely positioned to solve this problem?

At Relyance AI, our fundamental ethos from the company's inception has been “Privacy. It’s in the Code.” Relyance AI has been at the forefront of using patented intelligent code scanning techniques and triangulating that with specialized integrations to understand the data landscape, make sense of it from a compliance and a risk lens, and build more robust data protection programs. Our architecture and approach prime us to help our users solve AI governance as the next natural step. By using our best-in-class code scanning techniques, our integration capabilities, and our state-of-the-art NLP models for scanning contractual obligations, Relyance AI can help customers with:

  • Identifying and cataloging your AI systems and models: Relyance AI can determine which AI systems and underlying models are being used, where they live in your organization, what type of data is being fed into these systems and models, and any other associated metadata. We firmly believe that governance will be futile unless organizations solve this fundamental discovery piece at scale.
  • Identify compliance obligations and conduct assessments: Relyance AI can help you conduct AI risk assessments and identify compliance obligations based on the risk categorization of AI systems. Using our best-in-class NLP capabilities and homegrown models, we can enable you to review agreements and policies on a large scale, understand AI system usage, and track the safeguards put in place by your third-party systems.
  • Identify and resolve vulnerabilities that pose a risk: AI systems and models pose a massive security risk for most companies. These new attack vectors not only increase in your own application and product development areas that use AI, but they also increase in your supply chain. Your vendors are introducing AI capabilities to create value, increasing attack vectors for your organization. By helping create visibility around potential threats and data flows from your application's AI systems and those of your third-party vendors, we arm security teams with all the information they need to keep their crown jewels secure.
  • Continuous monitoring: Relyance AI is built with a continuous monitoring lens, and we will use the same philosophy and architecture to help you govern AI systems. Governance will only be effective if you match it with the speed of technology development and have a system in place that continuously monitors, updates, and proactively alerts throughout your AI landscape.
  • Building policies and controls: With the explosion in different rules and regulations around AI (like the EU AI Act, the Canadian AIDA, the NIST AI framework, or state-specific regulations like in New York or Colorado, to name a new), we recognize that every organization will interpret these differently in the unique context of their organization. Relyance AI can enable you with out-of-the-box policies and provide you the flexibility to define your own rules and policies to stay ahead of various compliance regulations

We look forward to embarking on this journey with you. Our ethos at Relyance AI has always been to advance technology to build best-in-class data protection programs. We are privileged and enthusiastic to be in this position to help our customers address the explosion in AI systems, the associated security complications, and the increasing regulation that comes with them. We’re committed to helping organizations navigate this new era and usher in the age of AI.

Blog Post

AI Governance: The Relyance AI Approach

In the wake of the EU AI Act's passage and amidst the burgeoning AI revolution, organizations worldwide are grappling with how to harness AI's potential ethically and responsibly. Relyance AI stands at the vanguard, ready to demystify AI governance with its innovative approach. This blog reveals how Relyance AI, leveraging its cutting-edge code scanning techniques and NLP models, provides a comprehensive framework for identifying AI systems, assessing risks, and ensuring compliance.

Aug 17, 2022

Get the whitepaper

Required field*

AI Governance: The Relyance AI Approach

The recent approval and passage of the EU AI Act has been monumental - and rightfully so - has raised many questions among various stakeholders. This recent approval comes on the heels of an astronomical explosion in the use of AI tools, models, and generative AI systems across the board. AI has been, and is poised to, increasingly continue as one of the most significant technology developments of our lifetimes (on par with the internet) and undoubtedly has everyone thinking about leveraging it. Organizations across every industry sector are beginning to approach this situation and figure out appropriate ways to incorporate AI in ways that respect their customers.

At Relyance AI, we are intimately familiar with AI and have heard a stream of questions from the broader community:

“I am not sure what my next steps should be. It’s overwhelming.”

“How will I keep up with the changing AI landscape when new models and capabilities are introduced daily?”

“Who should own AI governance in my company? Should it be the privacy team? Or the security team? Or both?”

We get it. It’s the wild west out there, but know you are not alone.

The Basics

There is a lot of content on AI Governance, but in simple terms, AI Governance includes the following steps. First, identify AI systems and models used by your application(s), the third parties in use, and the types of data flows that feed in and out of those. Second, gather visibility into the associated metadata around these systems to help you understand their risk and compliance profile, and clearly understand your compliance obligations. And third, take action on this information. At Relyance AI, we believe that AI governance and risk in the context of data protection are shared responsibilities between privacy, security, and governance teams, and collaboration is embedded into our platform to streamline that process for users.

For Privacy teams, in addition to the EU AI Act, the NIST Risk Management Framework, the recent Executive Order on AI, and other regulations like the Canadian Artificial Intelligence and Data Act, regulators across the U.S. (at the federal and the state level) and across the globe have been prolific in introducing legislation and being active to address artificial intelligence. It is clear that understanding AI systems, conducting assessments, understanding the data they process, and the risk they pose based on different controls from various regulations, as well as using this information to create transparency for end users, will be crucial.

For Security Teams, AI governance requires getting visibility into data flows and establishing policies, procedures, and controls to ensure that AI systems don’t introduce mission-critical vulnerabilities and are transparent, unbiased, and accountable. By integrating AI Governance into cybersecurity processes and practices, organizations can enhance their security posture by developing and deploying AI systems responsibly, thereby mitigating potential harm to their organization and customers. AI systems can bring in a host of new threats like data poisoning, model theft, model evasion, and more. It will be critical for security teams to gain visibility and prepare defenses for these new attack vectors.

Regardless of your role within the organization, effective AI governance can only begin if you know what your AI landscape looks like and when it changes. From there, different governance layers and policies can be applied to comply with regulations, mitigate risks, and, most importantly, keep your customer's data safe.

Why is Relyance AI uniquely positioned to solve this problem?

At Relyance AI, our fundamental ethos from the company's inception has been “Privacy. It’s in the Code.” Relyance AI has been at the forefront of using patented intelligent code scanning techniques and triangulating that with specialized integrations to understand the data landscape, make sense of it from a compliance and a risk lens, and build more robust data protection programs. Our architecture and approach prime us to help our users solve AI governance as the next natural step. By using our best-in-class code scanning techniques, our integration capabilities, and our state-of-the-art NLP models for scanning contractual obligations, Relyance AI can help customers with:

  • Identifying and cataloging your AI systems and models: Relyance AI can determine which AI systems and underlying models are being used, where they live in your organization, what type of data is being fed into these systems and models, and any other associated metadata. We firmly believe that governance will be futile unless organizations solve this fundamental discovery piece at scale.
  • Identify compliance obligations and conduct assessments: Relyance AI can help you conduct AI risk assessments and identify compliance obligations based on the risk categorization of AI systems. Using our best-in-class NLP capabilities and homegrown models, we can enable you to review agreements and policies on a large scale, understand AI system usage, and track the safeguards put in place by your third-party systems.
  • Identify and resolve vulnerabilities that pose a risk: AI systems and models pose a massive security risk for most companies. These new attack vectors not only increase in your own application and product development areas that use AI, but they also increase in your supply chain. Your vendors are introducing AI capabilities to create value, increasing attack vectors for your organization. By helping create visibility around potential threats and data flows from your application's AI systems and those of your third-party vendors, we arm security teams with all the information they need to keep their crown jewels secure.
  • Continuous monitoring: Relyance AI is built with a continuous monitoring lens, and we will use the same philosophy and architecture to help you govern AI systems. Governance will only be effective if you match it with the speed of technology development and have a system in place that continuously monitors, updates, and proactively alerts throughout your AI landscape.
  • Building policies and controls: With the explosion in different rules and regulations around AI (like the EU AI Act, the Canadian AIDA, the NIST AI framework, or state-specific regulations like in New York or Colorado, to name a new), we recognize that every organization will interpret these differently in the unique context of their organization. Relyance AI can enable you with out-of-the-box policies and provide you the flexibility to define your own rules and policies to stay ahead of various compliance regulations

We look forward to embarking on this journey with you. Our ethos at Relyance AI has always been to advance technology to build best-in-class data protection programs. We are privileged and enthusiastic to be in this position to help our customers address the explosion in AI systems, the associated security complications, and the increasing regulation that comes with them. We’re committed to helping organizations navigate this new era and usher in the age of AI.

Blog Post

AI Governance: The Relyance AI Approach

In the wake of the EU AI Act's passage and amidst the burgeoning AI revolution, organizations worldwide are grappling with how to harness AI's potential ethically and responsibly. Relyance AI stands at the vanguard, ready to demystify AI governance with its innovative approach. This blog reveals how Relyance AI, leveraging its cutting-edge code scanning techniques and NLP models, provides a comprehensive framework for identifying AI systems, assessing risks, and ensuring compliance.

Aug 17, 2022

Watch the video

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Sanket Kavishwar
Senior Product Manager