Enterprises need to adopt Governed AI yesterday

As more software providers seek to supercharge their platforms with AI services, those evaluating new tools must consider if those capabilities provide the native platform governance and configuration that large enterprises need. Normalized use of AI comes with huge risks across data security, compliance, and the potential for its misuse.

Enterprises that navigate these challenges effectively can realize enormous benefits, including a more efficient workforce and a stronger ability to retain top talent who expect to work with advanced technologies. However, enterprises - particularly large, risk-averse ones - are often held back by the complex landscape of AI solutions available to them. Many of these organizations face a paradox: they need AI to move forward, but they are wary of the risks posed by the technology. This is where the principle of Governed AI comes in.

Gartner highlights that 2024 will see AI as the ‘most important’ business technology. Meanwhile, McKinsey estimates that AI technologies could deliver up to $13 trillion in additional economic activity by 2030. Despite these growth projections, many large enterprises remain hesitant to embrace AI fully due to the potential risks.

The headlines covering the risk focus on job losses and a dystopian AI-agent dominant future. While these predictions may turn out to be accurate, the threats of data breaches and a lack of governance is a much more immediate concern. According to data breach law firm, Hayes Conner, 11% of the information that employees copy and pasted into ChatGPT is confidential, and as security attacks become ever more sophisticated, we can assume that bad agents are already attempting to draw out sensitive data from open platforms. However, without providing governed alternatives employees will continue to use AI tooling despite this security exposure.

Without safeguards, the likelihood of shadow IT - when employees bypass official channels to use unauthorized technology - rises. Shadow IT can create a tangled web of unsecured data, regulatory violations, and inefficiency. To prevent this, enterprises need a solution that allows them to use AI, but with the confidence that it is governed properly. That solution is Governed AI.

What is Governed AI?

Governed AI is the deployment of emerging artificial intelligence in a secure, controlled, and scalable manner, ensuring that organizations reap the benefits of AI without exposing themselves to undue risks. This framework enables enterprises to harness the power of AI with the necessary guardrails in place. Governed AI ensures that AI is used safely and securely by employing ring-fenced data, granular yet scalable permissions models, and strict information security protocols. Governed AI will also provide the means to effectively monitor and report on AI usage. By providing AI through an experience-layer with comprehensive analytics, large enterprises can drive adoption and further reduce risk by assessing usage across different audiences.

In the absence of Governed AI, large enterprises risk data leaks, non-compliance with regulations, and the spread of unauthorized AI usage across their workforce. This not only opens them up to legal and security vulnerabilities but has the potential to significantly impact employee and customer experiences. Governed AI is essential for ensuring that AI use aligns with corporate governance, data protection laws, and organizational standards.

The Essential Components of Governed AI

Governed AI is not just about implementing AI solutions—it's about making sure those solutions are deployed with the highest standards of security and governance. Here are the essential components of Governed AI:

1. Highest Information Security Standards

The foundation of Governed AI is compliance with the highest levels of information security and data privacy standards. For large enterprises, meeting certifications like SOC 1 and SOC 2, GDPR, ISO 27001, and the Cloud Security Alliance STAR Program is non-negotiable. These certifications and their corresponding infosec practices ensure that AI models and data are stored and processed securely, reducing the risks of breaches or unauthorized access.

When accessing AI within a high infosec environment, organizations ensure that their data - often sensitive employee or customer information - remains protected. This high level of security not only helps organizations avoid costly breaches but also builds trust with employees and customers alike.

2. Granular Permissions and Centralized Control

A critical feature of Governed AI is its use of granular yet scalable permissions, allowing enterprises to control who has access to specific AI capabilities and data, and when. Through a unified experience layer, AI is deployed in a scalable manner, tailored to different tasks, roles, or departments.

By granting access to AI in a controlled way, enterprises can pilot AI technologies with smaller groups before wider deployment. This phased rollout allows organizations to fine-tune their AI use, making adjustments based on early feedback without risking large-scale disruption or data leaks. Additionally, by managing permissions centrally, companies can control the costs associated with AI deployment - enabling access for only the most impactful audiences while maintaining flexibility.

Centralized governance is also critical for managing cost efficiency. AI, particularly advanced models like Generative AI, are resource intensive. With granular permissions, enterprises allocate AI resources where they are needed most, ensuring the optimal use of the technology without overspending.

3. Ring-Fenced AI for Secure and Specialized Use

One of the most critical aspects of Governed AI is its ring-fencing capability. In a large enterprise, the risks of using open AI models like those commonly found in consumer generative platforms like ChatGPT are significant. Open AI models are trained on vast, general-purpose datasets and can inadvertently leak sensitive information or create security vulnerabilities if not properly managed.

With ring-fenced AI, enterprises restrict their AI models to operate within a secure perimeter. This ensures that AI interactions remain compliant with corporate data policies and that sensitive information, such as HR records or proprietary business knowledge, is not exposed. Ring-fenced AI is purpose-built for enterprise use, meaning it focuses on specific, approved business functions, reducing the risk of accidental data exposure. A beneficial byproduct of this ring-fencing is that the focused view will generate better, more relevant results for your employees in the context of the enterprise. Additionally, ring-fenced AI stops shadow IT from becoming a problem by giving employees safe, compliant AI tools that meet their needs, eliminating the temptation to use unsanctioned, riskier alternatives.

Why Governed AI Matters for Large Enterprises

For large, complex organizations, Governed AI is not just a "nice-to-have" - it’s essential.

Retaining control over the employee experience has never been more crucial but without an employee experience platform with a Governed AI framework, enterprises open themselves to a host of risks. Those neglecting governance open themselves to data breaches, compliance violations, and inefficient AI deployments. As an AI powered intranet becomes more integral to business operations, enterprises must prioritize security, control, and flexibility.

Governed AI offers a controlled way to deliver AI across diverse teams, ensuring that every part of the organization can benefit from AI without compromising on security. By establishing strict governance, ring-fenced environments, and granular permissions, large enterprises harness AI’s potential while maintaining the trust of their stakeholders and adhering to the highest standards of corporate governance.

In a world where AI is rapidly becoming ubiquitous, an intranet or EXP with Governed AI stands as the gateway for large enterprises to safely and effectively adopt this powerful technology. With this approach, enterprises won’t get left behind in contrast to their equally ambitious counterparts and can rest assured their precious data remains secure. It is no longer a question of whether to implement AI, but how to implement it securely—and Governed AI provides the answer.