AI Seoul Summit: How Enterprises Can Comply With Safety Regulations Without Even Trying

At the recent AI Seoul Summit, ten individual countries plus the full European Union formed a consortium “to make sure AI advances human well-being and helps address the world’s greatest challenges in a trustworthy and responsible way.” This announcement, closely following the adoption of the EU AI Act earlier this year, which officially went into effect on August 1, highlights the increasing complexity enterprises will face as they scale AI operations globally. 

As more jurisdictions adopt new AI regulations worldwide, enterprises must navigate a rapidly evolving regulatory landscape. Those who sow the principles of responsible AI into every stage of AI operations will find it easier to comply with the expanding volume of directives to ensure humanity reaps the benefits of artificial intelligence without suffering AI’s potential harm.

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The Global Diplomatic Alignment on AI Standards and Governance 

The AI Seoul Summit rearticulated an international commitment to the principles of AI safety, first expressed at the UK AI Safety Summit in 2023. That meeting saw the creation of the Bletchley Declaration, a multinational agreement to address safe, responsible, and inclusive AI. The Seoul summit also saw the signing of the Seoul Statement of Intent, which aimed to create a global network of AI Safety Institutes and develop a unified International AI Safety Report. With 27 countries and the EU affirming the Seoul Ministerial Statement, further commitments were made to mitigate AI risks, including its misuse in weapons development. 

The US announced plans to host a meeting of the AI Safety Institutes network in San Francisco, while Korea committed to establishing its own AI Safety Institute. Building on the inaugural AI Safety Summit in the UK, these steps underscore a robust international commitment to safe and inclusive AI development. As precursors to numerous bills being considered in legislative bodies around the world, these international diplomatic efforts should be seen as harbingers of the growing interest in reining in commercial applications of artificial intelligence before it is impossible to do so.

Two Views of the Fluid Nature of AI Regulation and AI Optics

Enterprises scaling AI operations globally already feel the impact of the EU AI Act, the most significant legislation to date regulating AI practices. The consortium formed at the AI Seoul Summit adds another layer of complexity, underscoring that more AI regulation is undoubtedly on its way.

The AI Seoul Summit also saw a parallel pledge from global AI companies to uphold new safety standards around transparency and risk monitoring in their own AI operations. These are not binding or enforceable on any commercial enterprise. Still, public perception is becoming increasingly important for companies that want to lead in the ethical AI space. They must demonstrate a sustained commitment to observability, security, and privacy in all AI operations.

For enterprises scaling AI, reacting to this evolving regulatory landscape is impractical and unsustainable. Instead, enterprises must proactively institute responsible AI practices, including end-to-end model observability and data governance. Doing so ensures compliance with current and future regulations and enhances brand reputation while maintaining operational efficiency and encouraging innovation.

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Viewed pessimistically, the rapid evolution of AI regulation amounts to a growing headache for enterprises striving to constantly react to the changes while looking for the path of least resistance to keeping compliant. When viewed optimistically, however, all of this growing attention on AI safety can be leveraged as an opportunity: Enterprises that manage responsible AI properly turn their proactive posture into a competitive advantage. These companies that succeed in associating their brands with ethical AI set the standard for their industries and build trust in AI within the total addressable market they are courting.

Responsible AI Is Foundational to Mature AI

For all the hype that AI has received since ChatGPT burst onto the scene, somehow the race to scale AI has snuck up on so many of us. But there’s a right way to get to AI maturity, and for all the reasons mentioned above, responsible AI must be a core tenet.

Here’s a look at the elements of mature AI operations at scale:

• Hub & Spoke Operating Model: The distributed enterprise establishes an AI Center of Excellence where a centralized data science team pulls open source models from public registries, trains them on the company’s proprietary data, and makes these now-proprietary models available to regional data science teams via private model registries. These regional data scientists fine-tune the models on local data and then deploy and monitor them locally.
• Responsible AI Throughout the Model Lifecycle: The AI operations team builds model observability into every phase of the model lifecycle to reinforce transparency and reproducibility in AI operations. At the same time, strict data governance, privacy, and security principles ensure that AI inference delivered in edge environments will be highly relevant to each geography where the inference is served while ensuring that customers’ rights to data privacy and residency are always preserved.
• Platform Engineering Purpose-Built for AI Operations: Mature enterprises can have dozens or even hundreds of models in development and production at any given time. The way to manage so many concurrent moving parts is by adopting a platform engineering approach that abstracts away the complexity and automates the provisioning of infrastructure and tooling AI engineers need.

It’s important to emphasize that these are operational approaches rather than packaged solutions for getting to responsible AI, which must be organically developed to reflect the specific needs of the given enterprise. As such, all three aspects will look unique in each enterprise that embraces them.

Turning the Aspirations of the AI Seoul Summit into Sound AI Practice

Organizations scaling AI operations can’t afford to consider compliance with AI regulation apart from their plans for AI maturity, just as they can’t afford to treat compliance as a burden rather than an opportunity. The principles stemming from the AI Seoul Summit—ensuring safe, responsible, and inclusive AI—provide a roadmap for coming legislation. No matter where enterprises are on their journey to AI maturity, they must place responsible AI at the core of their AI operations.

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