AI has rapidly emerged as a key technology in the modern era. With its ability to automate processes and analyse data, AI has proven to be a game-changer for businesses across various industries. Specifically, AI as a service (AIaaS) is a relatively new trend in which companies provide AI capabilities as a cloud-based service, allowing customers to leverage AI technologies without investing in expensive infrastructure or hiring their own AI teams.

However, before jumping into AIaaS, it’s essential to consider this service’s legal, commercial, and technical aspects.

Legal considerations

Is the AI lawful?

No general international AI law currently exists. However, it’s worth considering the EU’s AI Act clause on prohibited AI in deciding whether your AI project is lawful. The thinking is that the Act will be the golden standard for AI regulation internationally.

Data privacy and security

AI systems typically require access to vast amounts of data to learn and improve. And often, this data is personal data. So it’s crucial to ensure that your AIaaS processes data in line with applicable data privacy regulations. You may also need to conduct an AI-specific privacy impact assessment if the data processing is a high risk to data subjects.

Liability and accountability

As AI systems become more prevalent, it’s best to consider who is responsible for any errors or damages caused by AI.

In most cases, liability will rest with the company providing the AI service. But it’s vital to understand your AIaaS agreement thoroughly because it may distribute liability differently or even disclaim liability.

Intellectual property

Ensuring that using AI does not violate intellectual property rights is crucial to prevent third-party claims and reputation harm.

Practically, you can do so by ensuring you and your service provider have the rights and licences to use any AI technology you incorporate into your products or services.

Commercial considerations

Managing costs

By leveraging AIaaS, you can avoid the upfront investment in hardware and software required to build your AI capabilities. Plus, by outsourcing AI services, you can reduce the cost of hiring and training your own AI teams.

Availability of services

AIaaS providers offer a range of services, and companies must ensure that the required services are available. Some AIaaS providers may specialise in certain areas of AI, such as computer vision or natural language processing. Companies must ensure that the selected AIaaS provider can provide the specific services they require.

Scalability

As your organisation grows, your AI needs will likely increase. So, your AIaaS provider must be able to scale its services to meet your growing demands.

Technical considerations

Service quality

You probably want AIaaS to be accurate and reliable. To do so, ensure your selected AIaaS provider has a proven track record of delivering high-quality services.

Compatibility

You should also ensure the AIaaS can integrate seamlessly with your existing infrastructure. The effect will be quick implementation and efficiency without requiring significant changes to your current processes.

Customisation

AIaaS providers offer varying levels of customisation, from off-the-shelf solutions to fully customisable options. So, it’s best to consider your unique needs and determine whether you require a customised solution or can leverage an off-the-shelf option.

Actions you can take next

  • Manage your AIaaS relationships by asking us to draft an AIaaS agreement for you.
  • Ensure your AIaaS agreements comply with applicable laws by asking us to review them.
  • Navigate the platform risks of AIaaS by asking us to draft an acceptable use policy.
  • Comply with data protection law for your AI projects by joining our data protection programme.