Algorithms in the Developing AI Landscape


Algorithms in the Developing AI Landscape

The growing popularity of algorithms and Artificial Intelligence

Algorithms have become indispensable tools for organizations in today's modern business landscape. Paired with rapid advancements in Artificial Intelligence (AI), the expanded utility of algorithms empowers businesses to unlock heightened operational efficiencies, spanning from enriched customer experiences to finely-tuned strategic planning. With these technological strides, assurance takes center stage, ensuring the responsible management of risks arising from algorithms and AI. This becomes especially crucial as regulators and the public scrutinize these developments more closely.

While harnessing algorithmic capabilities can yield numerous advantages for your business, there looms the genuine risk of misuse or inadequate control, amplifying exposure to legal, regulatory, and operational vulnerabilities. Recent years have underscored the consequences of faulty algorithmic risk management, illustrating the potential for reputational, regulatory, and financial harm.

The trend toward embracing Artificial Intelligence systems represents a departure from the traditional application of algorithms, shifting the landscape of associated risks in the market. Customer interactions driven by chatbots, AI-fueled healthcare screenings, or machine learning-based fraud detection in consumer spending patterns all carry the potential for direct harm to consumers. Paradoxically, these risks often remain concealed from end-users. In a technology arena characterized by ceaseless evolution, forthcoming regulations emphasize the need to validate AI development beyond mere algorithmic control assessments.

Here’s some of what algorithmic assurance can do for your business:

  • Provide a detailed, objective, third-party review of the code underpinning your algorithm to uncover hidden risks or unintended outcomes
  • Using advanced analytics, measure the performance of your algorithm under normal and stress-test circumstances to optimize and ensure resilience
  • Conduct a comprehensive process review and report on how people interact with your algorithms, what manual controls exist, and what alerts are set off when a malfunction occurs
  • Analyze not just what your algorithm is doing but also how, in order to ensure the logic of your robot accurately reflects the methodology and expectations of its human managers


Niels van de koppel

Niels van de koppel


Niels is an Audit Partner active in the TMT industry serving large (Listed) clients. He has a wealth of experience in auditing large international groups which report under Dutch GAAP, IFRS and US GAA... More