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Generative AI Governance Platform

Ensure Responsible AI Use Within The Enterprise With Generative AI Governance

An AI TRiSM Platform that empowers organizations to take control of their GenAI approach and ensure responsible and efficient deployment of Generative AI throughout the organization.

Unleash the Potential of Generative AI with AI Governance

As the use of Gen AI continues to grow, the importance of effective governance has become increasingly apparent – and enterprises are restructuring their C-suites, appointing dedicated CAIOs to shape these necessary standards. With Gen AI Governance, organizations can access a comprehensive suite of tools to manage risks, protect privacy, and implement policies while maximizing the advantages of AI technology. 

Why Generative AI Governance Matters

As the use of generative AI has skyrocketed, companies find that there is minimal visibility into who is using generative AI and for what purpose, creating critical GenAI observability gaps. In addition, the generative AI usage introduces legal, AI data privacy, intellectual property, and compliance risks that are challenging to monitor and mitigate. Further, security teams are unable to investigate generative AI related incidents, and business teams have no tools by which to discern the true impact of generative AI on productivity and process. That’s where Portal26 comes in.

The Power of Control: Generative AI Governance Within The Enterprise

Portal26 Addresses CISO Concerns Around GenAI Usage

When we launched our GenAI governance and TRiSM platform, we set out to provide enterprises with visibility into GAI software usage. This GenAI visibility capability allows organizations to accelerate their use of GAI by providing them with the insights needed to develop and implement generative AI governance strategies that reduce compliance, intellectual property (IP), privacy and other associated risks.

Uphold GenAI Policies And Compliance

Enforce GAI policies that are in line with your organization’s goals. Make sure that your Generative AI use complies with industry standards and internal regulations. With Portal26’s GenAI Governance capabilities, you can remain compliant with the ever-evolving landscape of GAI, while also developing your understanding of AI TRiSM.

Uncover GAI Insights Through Generative AI Monitoring

Utilize Portal26’s GenAI monitoring and forensics capabilities, and optimise your core business functions with our dynamic platform. Find anomalies, monitor performance, and analyse trends. Our Gen AI Governance Platform provides a 360-degree view of GAI use within the enterprise.

Portal26's Generative AI Governance Solution Provides Organization's With:

Risk Management
Gain visibility and control over enterprise-level Gen AI risks, protecting your organization from potential pitfalls.
Privacy Assurance
Enforce security protocols and privacy controls to ensure that confidential information remains secure.
Policy Enforcement
Make sure your policies for Gen AI are in line with your company's values and compliance needs.
Performance Monitoring
Keep track of AI performance and usage patterns, optimize results and allocate resources accordingly.

Experience Generative AI Governance Today

Are you ready to take your organization to the next level of responsible AI use? Schedule a live demo with our team of experts to discover how our enterprise GenAI governance platform can revolutionize your GAI strategy. Discover insights, enforce ethics, and safeguard your AI path.

Become a leader in Generative AI governance and set the standard for a responsible AI future. Your journey to AI excellence starts here.

Your GenAI Governance FAQs

Generative AI is a type of artificial intelligence system that generates new content, such as images, text, or audio, often using deep learning techniques. These systems are specialized in creating data rather than understanding or completing tasks. On the other hand, general AI is a system that can understand, learn, and apply knowledge across a wide range of tasks. 

In terms of usage, Generative AI tends to be controlled and deployed by employees to improve internal workflows and in turn, productivity. Conversely, General AI is less accessible to the masses - these kinds of technology are used within organizations by key figures such as IT managers and CISOs.

The former is shaping business operations across many verticals, and its applications are already creating distinctive competitive advantages. Everyday tasks are enhanced, as Generative AI encourages operational efficiency and versatility across core business functions - from data processing to content creation. The technology is helping businesses to work smarter, growing their bottom line as a result.

GenAI Governance is a key aspect of any GenAI strategy, and we’ve broken this concept down into some distinctive principles:

  • Transparency - Ensure transparency in AI decision-making processes and algorithms to build trust and understanding.
  • Accountability - Clearly define roles and responsibilities, holding individuals and organizations accountable for the development and deployment of AI systems.
  • Fairness - Strive for fairness and avoid biases in AI systems, promoting equal treatment and opportunities for all users.
  • Security - Implement robust security measures to safeguard AI systems from cyber threats and unauthorized access.

As with any framework component, there are various potential risks and challenges that influence ethical practice in regards to GenAI.

  • Bias and discrimination - GenAI systems may inherit biases from training data, leading to discriminatory outcomes.
  • Privacy concerns - The generation of realistic content raises privacy concerns, especially when it involves personal or sensitive information.
  • Regulatory compliance -  Evolving regulations and standards pose challenges in ensuring compliance and keeping AI practices up-to-date.
  • Understanding disparity/knowledge gaps - Users and stakeholders may not fully understand how GAI systems operate, leading to mistrust and skepticism.

 

Integrating ethical considerations at the earliest stages of Generative AI development is essential to proactively identify and mitigate risks, build trust with users and stakeholders, ensure legal compliance, and contribute to the long-term viability of AI systems by addressing societal concerns and fostering responsible development.

Being aware of ethical factors also means acknowledging the fact that some of these influences are always going to be present within the space that AI is deployed in, and by those it is deployed by. Bias is a perfect example of this, and we can apply it to the employees utilizing any form of Generative AI technology. Each individual has their own (often unconscious) biases, and they can impact the output generated in each case. In this way, organizations that want to enjoy the full benefits of Generative AI must account for bias from the offset, and find ways to manage it for each application. 

A model GenAI governance framework refers to a set of policies, procedures, and guidelines that govern the development, deployment, and use of AI models within an enterprise. We’ve shortlisted its key components below:

  • Ethical guidelines - Provide a clear outline of the ethical considerations and principles that guide AI model development and usage.
  • Transparency measures - Define how transparency will be met, including explanations of model decisions and disclosure of potential biases.
  • Accountability mechanisms - Establish roles and responsibilities, and specify who is accountable for various aspects of AI development and deployment.
  • Data governance - Define protocols for responsible data handling, including data privacy, security, and consent.
  • Risk assessment - Conduct regular risk assessments to identify and mitigate potential risks associated with AI models. 
  • Regulatory compliance - Ensure that the AI governance framework aligns with relevant regulations.
  • Continuous monitoring and evaluation - Implement mechanisms for ongoing evaluation and improvement of AI models to adapt to changing circumstances.
  • Stakeholder involvement - Involve stakeholders in the governance process to incorporate diverse perspectives and address concerns effectively.

AI is weaving its way into normality, and in the context of business operations, it is already creating unprecedented effects. From sparking new innovation and creativity, to unleashing automation for core tasks, the technology is being widely embraced across different industries. Simultaneously, AI solutions are constantly being developed to fulfill new needs, and in turn, the governance frameworks needed to sustain it are being prompted to fit this evolving demand. 

Companies that have invested in AI are now having to reassess their usage in light of new, ethical questions around applications. The consequences of not doing so have significant gravity, varying from prosecution to tarnished brand reputation. Having an adequate governance policy isn’t an isolated task - it requires constant review, adding to the responsibility that enterprises have in order to benefit from the technology in a compliant, safe, secure way.

Have more questions? Contact us at info@portal26.ai or schedule a demo to get personalized answers.

Download Our Latest Gartner Report

4 Ways Generative AI Will Impact CISOs and Their Teams

Many business and IT project teams have already launched GenAI initiatives, or will start soon. CISOs and security teams need to prepare for impacts from generative AI in four different areas:

  1. “Defend with” generative cybersecurity AI.
  2. “Attacked by” GenAI.
  3. Secure enterprise initiatives to “build” GenAI applications.
  4. Manage and monitor how the organization “consumes” GenAI.

Download this research to receive actionable recommendations for each of the four impact areas.