RBA Artificial Intelligence to Create New Banking Jobs

RBA artificial intelligence tools are transforming how Australia’s central bank analyses economic data, while the country’s benchmark cash rate sits at 3.6 per cent. The Reserve Bank of Australia recently acquired its first enterprise-grade graphics processing unit to develop advanced AI-driven analytical tools, consequently enhancing its ability to process information at scale.

What is artificial intelligence in banking evolving into at the RBA? According to recent analysis, generative AI alone could contribute approximately £45 billion and £115 billion annually to the Australian economy by 2030. The RBA AI systems now enable sharper analysis of more than 22,000 conversations with businesses, providing a clearer understanding of the country’s economic landscape. While many experts anticipate a net increase in jobs from this technological shift, the reality appears more nuanced. Some roles will be redefined, others might face displacement, and entirely new positions will emerge. This technological evolution continues the historical pattern where advancements have constantly reshaped labour markets.

RBA Deploys AI Tools to Enhance Economic Analysis

The Reserve Bank of Australia has developed sophisticated artificial intelligence systems that fundamentally change how economic data informs policy decisions. Governor Michele Bullock emphasises that these tools do not make policy decisions but enhance the bank’s analytical capabilities.

RBAPubChat Chatbot Supports Policy-Relevant Queries

The RBA has designed and begun testing an innovative AI-powered tool called RBAPubChat, which stands for ‘Conversation Hub for Analysis and Thought’. This intelligent chatbot helps staff formulate policy-relevant analytical questions and obtain useful summaries from the bank’s extensive knowledge repository spanning four decades. As analytical documents have grown exponentially since 1985, this system has become essential for accessing institutional knowledge efficiently.

RBAPubChat draws on nearly 20,000 internal and external RBA analytical documents and functions beyond a mere search tool. It provides comprehensive reviews of past work, contextualises new analysis, supports innovative thinking, and constructively challenges existing insights – ensuring analysts don’t “reinvent the wheel”.

AI Analyse 22,000+ Business Conversations

Over 25 years, the RBA has conducted more than 22,000 conversations with businesses through its liaison programme, generating over 22 million words of qualitative data. To harness this wealth of information, the bank developed a secure text analytics tool using natural language processing.

This system transforms qualitative text into structured data, allowing analysts to search, analyse and extract meaningful insights from business discussions. Furthermore, this tool enhances rather than replaces expert judgement, helping analysts understand business sentiments more effectively and efficiently. The technology enables teams to contextualise aggregated insights across themes or firms and compare them against historical patterns with unprecedented speed and precision.

Machine Learning Improves Wage Growth Forecasting

The integration of liaison-based textual indicators into model-based nowcasts through machine learning techniques has yielded remarkable results. Early implementations have demonstrated that this approach significantly improves the accuracy of wage growth forecasts, outperforming traditional Phillips Curve models.

Research published by the RBA indicates that text analytics offers three key capabilities:

• Rapidly querying the entire history of business liaison meeting notes
• Examining topic frequency, tone, and uncertainty in discussions
• Extracting precise numerical values from text, including firms’ reported wage figures

This interdisciplinary effort between data scientists and economists has proven crucial in ensuring the new tools’ relevance, accuracy, and practical utility. By combining structured statistics with rich qualitative insights, the RBA is building a more complete picture of Australia’s economic landscape.

Michele Bullock – AI Will Reshape Banking Roles

In a recent address at the Shann Memorial Lecture in Perth, Reserve Bank of Australia Governor Michele Bullock highlighted how artificial intelligence will profoundly reshape banking employment landscapes. Technological evolution has historically transformed labour markets, and Bullock emphasised that AI represents the next significant wave of this ongoing process.

Roles Redefined and Displaced

Bullock outlined a nuanced future for banking employment that extends beyond simple job creation or elimination. “As AI continues to reshape industries and economies, it is not just the tools and processes that are evolving – it is the very nature of work,” she noted. The impact will vary substantially across different roles and skill levels. Lower-skilled positions may decline in number, continuing a decades-long trend away from routine manual work. Moreover, research from Citigroup indicates the banking industry could be particularly affected, with 82.57% of roles potentially facing AI-led displacement.

New Job Categories

Despite potential job losses in certain areas, Bullock expects entirely new roles to emerge as the technology matures. Initial implementations may actually increase headcount as financial institutions design and embed new technologies, though modest declines might follow this as adoption matures. Banking professionals can future-proof their careers by accumulating knowledge about AI capabilities in applications like customer service, fraud detection and credit decisions. One particularly in-demand position will be for Quant Developers and Analysts, who will work with historical data to enable machine learning for business-critical decisions.

AI Enhances Human Expertise

Essentially, the RBA governor stressed that AI primarily serves to enhance human capabilities instead of substituting them. “This tool does not replace expert human judgement, rather it enhances it,” Bullock explained regarding the RBA AI implementation. Accenture’s analysis reveals that 73% of the time spent by US bank employees has high potential to be impacted—39% through automation and 34% through augmentation. Roles involving significant judgement, such as credit analysts or relationship managers, stand to be empowered by AI tools that help prepare for and conduct meetings. Additionally, Bullock emphasised the importance of government investment in training and education programmes to support workers through these transitions.

Related Article: AI in Finance: Good or bad for World of Financial Services in 2024

RBA’s AI Evolution

RBA’s AI Evolution extends well beyond economic analysis tools. The central bank’s internal operations have undergone substantial transformation as artificial intelligence and coding capabilities become increasingly embedded in daily workflows.

1 in 4 RBA Staff Code Daily

Staff capabilities at the central bank have evolved markedly as technical skills become fundamental to operations. Currently, approximately 25% of RBA personnel engage with coding as part of their routine responsibilities. This reflects the ongoing importance of data science and computational methods in central banking operations.

AI-powered Coding Tools Improve Efficiency

Subsequently, the bank has implemented several AI-augmented coding platforms that enhance productivity. These tools automatically suggest code completions, identify potential errors, and streamline development processes. Consequently, staff can build analytical applications more rapidly and with fewer technical barriers, enabling them to focus on higher-value interpretative work.

Secure Tool Unlocks Text Insights

The RBA has also developed proprietary text analysis systems that operate within secure environments to maintain the confidentiality of sensitive economic information. These tools transform unstructured data from various sources into actionable intelligence. Meanwhile, natural language processing algorithms help identify emerging patterns and outliers in business sentiment that human analysts might otherwise overlook.

This technical development signifies a significant change in the way central banking functions, moving away from traditional economic research and towards data-driven decision support that integrates artificial intelligence and human knowledge.

Workforce: Challenges & Opportunities Ahead

Financial institutions worldwide face profound workforce transformations as artificial intelligence reshapes traditional banking operations. Citigroup research indicates the banking industry will be hardest hit by AI adoption, with 82.57% of roles at risk for displacement.

Lower-Skilled Roles Decline

Back-office functions, customer service positions, and routine data processing jobs face the most significant disruption. Entry-level positions show particular vulnerability, with Gartner research indicating 52% of entry-level banking roles could be impacted by generative AI. This continues a decades-long trend away from routine manual tasks. However, these statistics represent task automation rather than complete job elimination—the distinction remains crucial for understanding future employment patterns.

Demand for Higher-Skilled Roles Grow

Nonetheless, PwC’s analysis reveals augmentable jobs—where humans work alongside AI—grew 47% across all industries between 2019 and 2024. The financial sector actively seeks candidates with hybrid skillsets combining technical expertise with people leadership capabilities. Demand has grown for professionals proficient in data analytics, AI ethics, and digital customer service.

Training and Education Programmes Essential

Above all, successful navigation through this transition requires investment in employee development. Organisations need strategic approaches to workforce planning, beginning with recruitment and evaluating openness to reskilling programmes. In Australia, human capital remains the genuine differentiator, with targeted upskilling programmes and academic partnerships crucial for closing the AI-talent gap. Indeed, 87% of finance professionals believe they need to develop new skills to remain relevant.

Conclusion – RBA Artificial Intelligence

The evolution of artificial intelligence within Australia’s central bank represents a significant shift in how economic data shapes policy decisions. Throughout this technological transformation, the RBA has developed sophisticated AI systems that enhance rather than replace human expertise. Consequently, their analysts now process vast amounts of information with unprecedented efficiency while maintaining the critical judgment that underpins sound economic governance.

Though concerns about job displacement remain valid, evidence suggests a more balanced outcome lies ahead. Undoubtedly, certain banking positions will undergo substantial changes as routine tasks become automated. Nevertheless, the financial sector simultaneously creates new roles requiring hybrid skillsets that combine technical knowledge with interpersonal abilities.

Banking professionals who prepare for this transition stand to benefit significantly. Accordingly, those who develop AI literacy alongside their existing expertise position themselves advantageously in the evolving job market. Meanwhile, financial institutions that invest in employee development create competitive advantages through enhanced analytical capabilities.

Achieving success as AI continues to transform the banking industry will require striking a balance between technical innovation and human skill. Therefore, the future of the banking industry appears neither dystopian nor utopian. Instead, it presents an opportunity for meaningful transformation that ultimately strengthens Australia’s economic resilience through better-informed policy decisions and more efficient financial services.