Human-centred AI in Banking and Beyond

Artificial intelligence (AI) technology is advancing faster than expected. A recent report from the McKinsey Global Institute indicates that GenAI will create immense economic value for businesses. The report estimates that GenAI could add the equivalent of US 2.6TN - US 4.4TN annually across 63 analysed use cases, potentially doubling if we include its impact on software beyond those specific use cases. Furthermore, GenAI has the potential to automate 60-70% of employees' current work activities, substantially impacting labour productivity. However, as it becomes more widely used, some fears prevail among us. The primary ones are that it will make humans obsolete and that we will lose control to technology.?

In this article, I talk more about AI’s capabilities and limitations, how employees can prepare for the future workplace, and expectations from the AI space.?

People’s Place in the Future of Work

The Pace of Change

As we stand on the precipice of a new era marked by technological innovation, the industry finds itself at the crossroads of reinvention. The sudden rise of GenAI in the past year has sparked both excitement and apprehension among workforces worldwide. Analysing individual skills rather than entire job roles reveals that almost every profession can be influenced in some way by GenAI.?

Recent insights from Indeed’s Hiring Lab shed light on the nuanced impact of GenAI across various professions. While roles like nurses and care workers remain relatively untouched, others such as software development teeter on the edge of profound transformation.?

Embracing Creativity to Drive Growth

The AI shift presents an opportunity to revisit our approach to skill development. While specialist skills have always been valued for their depth and expertise in specific areas, adaptability, critical thinking, and collaboration are gaining increasing recognition as essential skills in the evolving landscape shaped by AI integration. The liberation from routine tasks paves the way for meaningful human interaction and fosters a synergy that machines cannot replicate.

The first step to AI adoption is to make the technology less frightening to workers.?

Building the AI Road

Embarking on the journey of integrating AI into the organisational fabric requires a well-thought-out strategic roadmap. Recognising the need for upskilling is definitely the first step. Leaders must go beyond recognition and instil a sense of urgency to foster a narrative aligned with the company’s purpose. This necessitates a cultural shift within organisations where employee engagement and change management become focal points.

Developing and acquiring AI talent in the banking sector

The McKinsey Global Institute predicts that the integration of GenAI in the banking sector could yield an annual value ranging from US 200BN - US 340BN.

Integrating technical talent with business leaders creates an environment conducive to developing scalable, GenAI solutions. By harnessing AI’s capabilities, banks can revolutionise customer service, fortify security measures, automate tasks for efficiency, pioneer innovative offerings, and enhance data management. This strategic leverage ensures streamlined processes and lower costs to position our institutions at the forefront of innovation in the dynamic financial landscape.

Update Control Measures?

Recognising the potential of GenAI in the banking sector mandates an overhaul of risk and model-governance frameworks. Introducing new controls addresses the risks associated with AI applications and ensures the responsible and effective utilisation of AI technology.

Currently, banks tend to bring in SMEs to validate model outputs. To ensure strong controls, banks can develop automation, validation methodologies, and playbooks.

Near-Term Development Outlook

In the near-term, AI capabilities will shift from reactive to proactive as they gain autonomy and proactivity. Besides agentic AI - advanced systems that can act independent of direct human intervention -, the tech will expand beyond traditional single-mode data processing via multimodal AI, processing sensory information through visual and auditory input. To reduce AI hallucinations, retrieval-augmented GenAI (RAG) will become increasingly prevalent, enabling language learning models (LLMs) to access external information, as well as produce more accurate and contextually aware responses.

While the technology becomes more accessible, shadow AI - tech use without explicit approval or oversight - will also become increasingly common. Shadow AI negatively impacts organisations through risk of data loss, poor configuration, security breaches, inconsistencies in resource utilisation, and ineffective management.?

Charting the Path Ahead – Challenges, Opportunities, and Preparation

While the nascent technology shows promising potential for boosting productivity, revenue growth, and individual incomes, these gains will be unequally distributed as wealthier countries can afford to implement and develop AI at a faster pace than their poorer peers. Disparities will also widen between younger and older generations as the former’s generally better adaptivity towards AI and other digital technologies will benefit them more than their counterparts. These discrepancies mark the coming years as an era where compliance and regulatory development take centre stage. Besides the creation of social safety nets and re-skilling workers for AI adoption, refining policies and procedures will be necessary to ensure responsible, equitable, and ethical AI usage.

Proficiency in algorithms, deep learning, cloud computing, cybersecurity, data analysis, and programming languages will be paramount. These skills are essential for various AI careers, enabling professionals to design, implement, and maintain AI systems effectively. Additionally, creativity, complex problem-solving, and social skills will become increasingly important as leaders empower employees to influence AI plans, leveraging both technical expertise and human-centric abilities. The journey into the future of work demands a measured and insightful approach. Balancing technical prowess with emotional intelligence, adhering to regulatory frameworks, and fostering a culture of responsible AI usage are the cornerstones of navigating AI in the financial services industry.

In Conclusion

With almost 40% of global employment exposed to AI, a broad understanding of AI concepts is invaluable. Individuals should also consider specialising in specific areas of interest or relevance to their career goals. Identifying niche areas within AI (such as computer vision, natural language processing, and reinforcement learning) and investing time in mastering them will allow workers to enhance their output through technological assistance. It can also help workers develop expertise in specialised domains to differentiate themselves in the job market and capitalise on emerging opportunities.

As leaders, we are not just witnesses but architects shaping a future where human ingenuity and technological innovation meet for sustainable growth and competitive advantage.