It’s 1984, I’m a schoolkid sitting in the Roxy theatre in Parramatta, watching the James Cameron film Terminator. It’s full of jump scares, tension and suspense, but the hero seemingly wins out in the end. 

Cut to 1991, an idealistic university student watching Terminator 2 at George St cinemas in Sydney. By this age I have realised that if we can imagine it, we can make it, and that leaves me with an unsettled feeling about the future for humankind. 

Jump to 2026 – the Age of AI. Machine Learning has everyone talking – productivity increases and time savings by replacing repetitive or mundane tasks, accelerating software development and mass data analysis. The opportunities are potentially boundless. 

What’s the Downside? 

Unfortunately, with technology advances come new challenges. Recent cases in point 

• Intellectual property ownership (think authors of books or research) is being challenged by AI accessing everything that is published. 
• Human capacity to think for ourselves, make decisions or be creative is reportedly reducing.  
• Influencing the outcomes of elections using deep fakes in digital media. 

Leadership Requires Good Governance 

The legislation and governance around AI use and development might be seen by some as red tape – just there to slow things down – but organisations using and developing AI systems have a responsibility to consider their impact on individuals, groups and societies. ISO 42001:2023 goes so far as to require this impact to be assessed and documented. 

Governance is not a one off activity, and it is not just for large organisations. But if you are using or developing AI there needs to be a life cycle approach. Starting with the purpose of the system, governance is also required for data quality and provenance, testing and validation, transparency for affected stakeholders, human oversight, third-party dependencies, deployment conditions, post-deployment monitoring, and retirement. 

Where to start? 

Start by understanding where AI is being developed, embedded or used across the organisation. Ensure accountability is clear and people are competent to govern AI, (not just develop or implement it). Of course, organisations must implement risk management processes, but top management and boards must be interested in the results to drive real uptake. 

It’s exciting times across all industries right now! With great risk comes great opportunity. Let’s make this a success not a movie plot.