Join FSU
Sign in

AI in finance:
transparency, voice, fairness

The FSU is leading the way to ensure artificial intelligence (AI) is used ethically across the finance sector. 

AI is transforming how decisions are made, how work is done and, in some cases, replacing jobs. As it becomes more embedded in our industry, it’s vital that workers have a genuine voice in how these technologies are introduced and used.

AI in the finance sector: The worker perspective (Version 2)

Our new report, AI in the finance sector: The worker perspective (Version 2), spotlights how AI is rapidly changing work across the finance sector - and why workers must have a say. It draws on a largescale survey of finance sector workers to show that while use of AI is surging, many workers feel increased job insecurity, inadequate support/training and a lack of meaningful consultation.

The findings make clear that unless AI is adopted with transparency, accountability, and worker rights front and centre, efficiency gains risk coming at the expense of fairness and wellbeing.
Download here

Get involved

We’re building a strong, united voice to advocate for the responsible use of AI that benefits workers. Join the movement by signing up to get involved and help shape the future of work in finance.

Get involved

Priorities for ethical AI adoption

AI should be used in a way that:

Enhances the dignity of work:

AI should improve the quality of our work and lives, not just corporate profits.

Shares the benefits with workers:

Productivity gains from AI should lead to better pay or reduced working hours for workers, such as a four-day work week.

Promotes transparency and accountability:

Employers must be open about how AI is used, ensuring workers can understand and challenge AI-driven decisions.

Protects jobs and provides retraining:

There should be a pause on job losses due to AI, and workers should be supported with retraining to transition into new roles, including the creation of roles in specialised areas of AI usage.

Key risks of AI in the finance sector

Worker surveillance and monitoring

The use of AI for worker surveillance in the finance sector has become increasingly pervasive. AI programs can track every aspect of an employee's workday, from keystrokes to time spent on specific tasks. While employers may argue that this level of monitoring improves productivity, it raises serious ethical and privacy concerns.

Workers often have little or no knowledge of how they are being monitored or what data is being collected. This lack of transparency can lead to a sense of constant scrutiny, contributing to stress and anxiety among employees. Furthermore, when AI is used to evaluate worker performance, the reliance on given information can result in a narrow and potentially misleading view of an employee's contributions. This "black box" surveillance not only undermines trust but also creates an environment where workers feel dehumanised and undervalued. 

Job losses due to automation

As AI becomes more capable, there is an increasing risk of job losses within the finance sector. Roles once performed by humans, particularly those requiring lower levels of education and training, are increasingly being automated. This trend not only threatens the livelihoods of many workers but also disproportionately impacts those in lower socioeconomic groups, increasing inequality.

The finance sector could see a significant shift in the demand for human roles, with fewer opportunities available for workers who are unable to transition into new, AI-focused positions. Without proper planning and support, these changes could lead to widespread job losses and economic instability for affected workers. 

Lack of transparency and explainability

One of the most significant concerns with AI in the finance sector is its lack of transparency, often described as a "black box" problem. AI systems make decisions based on complex algorithms that are not easily understood by humans, including those who are directly impacted by these decisions.

This lack of transparency can lead to biased outcomes that are difficult to detect and correct. For instance, when AI is used in lending or hiring decisions, it may inadvertently reinforce existing biases, such as those related to gender or ethnicity. Moreover, the inability to explain how decisions are made erodes trust between employers and workers, creating a power imbalance where workers have little recourse to challenge decisions that affect their careers and livelihoods. 

Inadequate regulation

The rapid pace of AI development has outpaced the existing regulatory frameworks designed to protect workers and ensure fair practices in the workplace.

Current regulations do not adequately address the unique challenges posed by AI, such as the potential for AI-driven decisions to bypass human oversight. This regulatory gap is particularly concerning in areas like worker surveillance, performance management, and job security. For example, when AI systems are used to monitor employee productivity or to make hiring and firing decisions, the lack of clear guidelines can lead to unfair or even discriminatory practices. The finance sector, which is already highly regulated, faces additional challenges in ensuring that AI technologies are implemented in a way that upholds ethical standards and protects workers' rights.

What does ethical adoption of AI look like?

Sharing the benefits of AI with workers

The FSU advocates for legislation that ensures the productivity and efficiency gains from AI are shared between workers and employers. One of the ways to ensure this is through shorter working hours, such as introducing a four-day work week. This would allow workers to benefit from the efficiencies generated by AI, rather than simply increasing corporate profits.

Active government involvement

The FSU believes that the government should take an active role in understanding and regulating AI. This includes hosting forums to explore how employers plan to introduce and use AI in their workplaces, as well as monitoring the use of AI technologies to prevent discriminatory practices, such as exacerbating the gender pay gap or limiting opportunities for minority workers.

Protection against job losses

The FSU calls for a three-year moratorium on job losses due to AI, allowing time for employers to identify roles at risk and for workers to receive retraining. This approach also recognises the potential for new roles to emerge in specialised areas of AI usage and ensures a fair transition for workers whose roles may be affected by AI.

Transparency and the right to an explanation

The FSU calls for the introduction of legislation that grants workers the right to an explanation of how AI-driven decisions are made, especially in contexts like hiring, promotion, and performance management. This legislation should be modeled after existing European laws, ensuring that workers can understand and challenge decisions that affect their careers and livelihoods.

Legal reforms for AI decision-making

The FSU recommends a review of the Fair Work Act 2009 to identify how AI decisions can be integrated into legal frameworks while maintaining employer accountability. Also, changes to Work Health and Safety laws are necessary to ensure that employers are held liable for decisions influenced by AI, particularly those related to performance, conduct, and safety.

Prohibition of surveillance on union communications

The FSU strongly advocates for a prohibition on any surveillance or monitoring of communications between a trade union, its delegates, members, and prospective members. This is essential to protect the privacy and integrity of union activities and ensure that workers can engage with their representatives without fear of being monitored or penalised.

Updating industry awards

Finally, the FSU supports a review of the Banking Finance and Insurance Award 2020 to better align it with contemporary practices in the finance sector. This review should include adjustments to ensure accurate and transparent pay banding that reflects the realities of modern work environments. With AI improving workplace efficiency, it’s time to review and update antiquated work practices. The standard working week, which has remained largely unchanged for more than 150 years, should be revisited, and discussions about the future of work, such as adopting a four-day work week, should become a priority.

Resources and submissions

In November 2024, the FSU undertook a survey of workers in the finance sector to get a snap shot of their attitudes and sentiment toward AI in the workplace and understand their concerns with the rise of AI technology. 

Approximately 2200 finance workers responded to the survey from across the country and the sector. The results have been summarised in this report, and our findings outline what the data tells us about the future of the finance sector.

Download report

Roadmap to a digital just transition

Flyer: A digital just transition

The FSU's submission to the Victorian Inquiry into Workplace Surveillance highlights the pervasive and largely unregulated surveillance of finance sector workers. It raises concerns about constant monitoring of worker activities, communication, and movement, often with no transparency or consent. The submission also addresses the role of AI in analysing surveillance data, potentially leading to flawed decision-making and worker stress. 

Read submission here

The FSU's submission to the House of Representatives Standing Committee on Employment, Education and Training's inquiry into the digital transformation of workplaces addresses the increasing use of AI in the finance sector. The FSU emphasises that the benefits of AI must be shared with workers, advocating for transparency in AI's usage and data handling. It also highlights concerns over job displacement, wage setting, and the need for robust legislation to protect workers from adverse effects, including unfair dismissals and lack of clarity on decision-making processes. 

Read submission here

The FSU's submission to the Select Committee on Adopting Artificial Intelligence focuses on the impact of AI adoption in the finance sector. The submission stresses that while AI can increase efficiency and create specialised roles, there are significant risks such as job losses, lack of transparency, and biased decision-making. The FSU advocates for regulation to ensure that workers benefit from AI-driven productivity gains and that decisions affecting workers' employment are made with human oversight. 

Read submission here

The latest on our campaign

Content will show on frontend.

BECOME AN FSU MEMBER TODAY.

When you join the FSU, you get access to expert workplace support whenever you need it. From pay and conditions to restructures and workplace disputes, we help you understand your rights. You'll receive representation where it’s needed and access to exclusive member benefits that add value beyond the workplace. If something isn’t right, or you simply want clarity about your options, you don’t have to navigate it alone.
Join FSU
Proudly supported by:
The Finance Sector Union respectfully acknowledges the Traditional Owners of the land on which we live and work, and pay respect to First Nations Peoples and their Elders, past and present.
Authorised by Julia Angrisano, Finance Sector Union of Australia, Level 13, 380 La Trobe Street, Melbourne, VIC 3000.
Copyright © 2026 Finance Sector Union (FSU). All rights reserved.
Privacy policy Site disclaimer

How we can help ?

I’m in! What’s the plan?

If AMP isn’t going to come to the table to negotiate our conditions with us, then we’ll need to force them.

And we will do that by securing a majority support determination (MSD). That sounds complicated, but all it means is that a majority of people working at AMP (or in a particular business area of AMP) vote to say they want to bargain – then AMP is legally obligated to negotiate. Of course, there are some legal hoops we need to jump through, but right now the most important thing you can do is click here to join us.

Now is the time to get as many of our colleagues involved and engaged in our campaign as possible.