AI guardrails - the essential reflection of a company’s standards, policies and core values
As the European Union's AI Act comes into full force in 2026, businesses across multiple jurisdictions will face a critical but often overlooked challenge – the lack of standardisation in AI regulation within a globalised economy. While much of the discussion around AI regulation focuses on national policies and the ambitious and far-reaching EU AI Act, the reality is that companies operating internationally must navigate a fragmented regulatory environment, which creates compliance uncertainty and risk.
AI-driven businesses, particularly in financial services sectors, rely on automated decision-making for data analysis, risk assessment, lending, predictive modelling, and fraud detection. However, the absence of a globally harmonised regulatory framework means that while they might meet compliance requirements in one country, they could inadvertently breach them in another.
A financial institution headquartered in Europe, for example, could rigorously implement AI compliance measures under the EU AI Act but fail to meet the unique requirements of the United States or the UK, which have based their AI regulations primarily on the common law method of addressing issues as they are identified. In China, the emphasis is on governing and managing online information, security – in particular, the protection of personal data – and using algorithms to individuals.
This inconsistency across countries has led to an environment full of compliance blind spots. However, the pace of AI innovation has meant that despite being vulnerable to legal challenges, there is little to prevent companies from developing AI applications that meet the rules in their own country, regardless of whether they break the rules elsewhere.
This is dangerous for any sector, but checks and balances are essential in highly regulated industries, such as financial services. That is why organisations need to implement guardrails for their AI systems.
Setting AI guardrails
As AI applications become more prevalent and autonomous, organisations need to rely on their accuracy, reliability, and trustworthiness. This is why AI governance frameworks and guardrails are becoming essential tools for developing secure and responsible AI applications.
These tailored frameworks have, to date, primarily been used to prevent Generative AI applications from creating offensive, discriminatory output, but their potential is much greater. 'Governance' guardrails, for example, cut risk by ensuring that AI systems comply with corporate policies and accepted ethical standards and legal mandates. Putting in place a 'role' guardrail means that AI systems personalise their actions according to individuals, considering their particular requirements and rights. To ensure AI-driven processes and workflows are conducted according to best practices, 'performance' guardrails can be implemented to boost efficiency and quality. And when it comes to keeping AI-generated content on-brand, 'brandkey' guardrails work within accepted corporate values and missions.
Let's look at how AI guardrails can be used to reduce compliance risks. In the US, it is illegal for AI systems to provide financial advice. Suppose an EU-based financial company wants to ensure it is meeting US regulations, regardless of what may be acceptable in its home country. In that case, its front-of-shop operations must take action to ensure customers cannot trick their conversational AI – such as a website chatbot – into delivering investment guidance. Putting in place an AI guardrail to verify the internal compliance of AI-generated responses before they are provided to customers will prevent the law from being broken and mitigate the risk of regulatory action. In more general commerce environments, AI systems also need to clearly understand the rights and personas of the people they are interacting with. This helps to avoid cases such as the person shopping for a car online who is renowned for tricking a car dealer's conversational AI into cutting the price tag to just one dollar!
Taking an ethical approach
While guardrails are not designed to take the place of national or international AI standards, what they do offer is a way for companies to facilitate trust and adoption of AI tools. They are an immediate route to ensure accountability and build awareness of regulatory loopholes as the regulatory landscape takes shape. Setting consistent ethical standards that reflect known legal requirements across global markets will guard against the systemic vulnerabilities currently putting companies in danger.
As AI becomes increasingly central to business operations worldwide, it is incumbent on them to take the impact and implications of AI as seriously as they take the opportunities it affords. Meanwhile, policymakers must prioritise global cooperation to ensure that AI innovation does not outpace ethical and legal safeguards. Only through standardised AI oversight can companies operate with clarity, protect consumers, and financial markets remain stable in an era of rapid technological advancement.
