​The spectre of artificial intelligence (AI) has been unleashed and there's no going back. But as self-learning technologies continue to spark innovations and big data breakthroughs, there is a growing call to set boundaries and expectations that will keep the inherent risks of AI in check.

This is no easy challenge. Intelligent algorithms (IA) and machine-learning (ML) technologies are advancing beyond the scope of current regulations and governance models. To keep pace, the following report explores how AI is being used by organizations worldwide and the legal, ethical, and logistical implications therein.

There's no denying the value of AI. Many Canadian organizations are already using machine-learning tech to automate key operations, generate critical insights, upgrade customer interactions, and inform strategic decisions. Financial institutions, for example, are leveraging AI programs to validate and forecast critical-yet-onerous activities, while healthcare specialists are using AI models to diagnose, predict, and address public health threats. Meanwhile, commercial organizations of every stripe are using AI to read their respective markets and define more profitable and sustainable strategies.

These advantages come with risks. With AI, ML and IA on the rise we must ensure they're being built with the most accurate, unbiased, and relevant data available. Guidelines are also needed to ensure AI continues to be ethical and resilient, and aspects of model-drift are continuing to be monitored and addressed in a timely manner.

The need for AI governance is clear. While international peers in the US, UK, and Estonia are showing the way, there is no clear consensus globally on best practices to guide the way. For our part, KPMG's AI in Control solution provides our clients and industry peers with an approach to adopting AI based on best practices across four main pillars: integrity, explainability, fairness, and resilience. Our view is that it's not just about using AI to get ahead; it's about doing so in a way that maintains trust and delivers the intended outcomes.

Promisingly, Canada is home to a burgeoning network of AI trailblazers, academics, and consortiums to become a leader in AI. Our next step is working with our public and private sector peers to establish clear and agreed-upon standards for AI governance. Ahead, we make a compelling case for global collaboration and bringing public and private sector stakeholders together to position AI as a force for positive change.

Related resources