Amid the growing need among organisations and their respective finance teams to harness AI and its promises, the case for responsible AI usage increases.
According to Intuit, against this backdrop, organisations should prioritise four things in their financial applications: fairness, security, compliance, and transparency.
This begins with setting and sticking to an ethical framework, as the technological advancement grows fast, but is prone to algorithmic bias.
Intuit says this happens when a model is trained on datasets that already contain bias, causing the outputs to be unfair or discriminatory.
Security is another consideration, as AI models are often trained on sensitive or confidential data. More quality data means greater insights, but financial leaders need to be careful with how they collect, store, and use that information, as there is an increased risk of exposing that data to cybersecurity threats or digital breaches.
Finance leaders must also take note of being open with customers and stakeholders about how and when AI is being used, particularly in high-stakes financial decisions.
Moreover, the regulatory landscape around AI in the finance industry is still taking shape, and it should be noted that organisations that build compliance into their AI practices early will be better positioned as rules and expectations firm up.
For future finance and accounting professionals, Intuit says learning AI skills can be considered as more important than ever.
AI-related skills that could help make one more competitive include:
- Programming languages (like Python or R)
- Machine learning
- Data science/data analysis
- AI product management
- Software engineering
