AI Compliance Challenges Businesses Face

Widely reported, AI is a game changer! We’ve understood some of the benefits as many companies share stories of process automation and efficiency gains however, we’ve really only just started to scratch the surface of what is possible.

With this data and information flowing there are a growing number of concerns around compliance in the context of AI. We’ve been working with some of our clients to understand where some of these challenges may surface or be relevant for them.

With that, I wanted to share those uncovered to date in the hope it’ll help you also to keep in mind and find answers pertinent to your Organisation. This isn’t an exhaustive list but just a few pointers to help us all on the Data and AI journey…

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Data Privacy and Security Concerns

AI systems rely on vast amounts of data, which raises significant concerns about data privacy and security. Compliance with data protection regulations like GDPR, APP and, CCPA is a minimum. Any AI tools that process personal data must have solid mechanisms in place to secure the data and ensure it is used ethically and legally.

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Algorithmic Bias and Fairness

AI algorithms can mistakenly exacerbate biases already present in training data. This could create unfair or discriminatory outcomes, particularly in areas such as HR (hiring), Finance (lendings), and of course in law enforcement. Audits can help to uncover and eliminate bias and compliance with anti-discrimination laws.

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Transparency and Explainability

There is often a lack of transparency in AI models, making it difficult to understand how specific decisions are derived. This can pose several compliance challenges, particularly in regulated industries. Hence the need for auditable transparency and explainability.

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Third-Party Risk Management

Third-party AI tools and services, can be super useful for a business however they can introduce additional compliance risks. Audit the third-party providers to ensure that they also adhere to the same compliance standards as your organisation.

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Intellectual Property and Data Ownership

Intellectual property (IP) and data ownership is a hard problem to solve give the large amounts of data available and used. Data used to train AI models may come from various sources, raising questions about who owns the resulting models and any insights gained. Watch this space as it evolves!

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Regulatory Changes and Adaptation

Regulations for AI continually evolve. Keeping up with these changes can be a job in it'self! The need to adapt AI systems to comply with new regulations is a challenge. There needs to be a regular review of regulatory changes and appropriate changes made to adapt accordingly.

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Over-Reliance on AI

Human oversight is essential to ensure that AI systems are functioning correctly and making decisions that align with regulatory requirements and ethical standards.

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Addressing these (and many more) challenges can significantly help businesses when looking to navigate an ever changing AI landscape. The complexity can often deter organisations from using AI technologies. Frameworks can assist in utilising these responsibly and effectively.

Contact me to hear more about our approach and see if we can help you to unlock the true power of your investment and environment.

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Argenti , founded in 2010, previously known as ICM Consulting and built on an insatiable thirst to solve complex.

We are Data and Application Architects. Our team leverage Enterprise Architecture to enable outcomes that drive efficiencies and optimisation.

We automate the mundane an unshackle your team from low value work. We provide you the ability to do more with less.