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Michael Williams, Deloitte Partner in the Financial Services practice assesses the impact of artificial technology on the workforce following a joint study with the World Economic forum.
As executives, policy makers and employee groups grapple with the inherent uncertainties of Artificial Intelligence, the recent World Economic Forum (WEF)/Deloitte study into how artificial intelligence (AI) is transforming financial services[i] is very timely.
To help clarify what AI can do, the Deloitte/WEF study agreed that Artificial Intelligence applies to a suite of technologies that can detect patterns, recognising (ir)regularities. It can determine the probability for future events and by generating rules from specific profiles, apply general data to customise and optimise outcomes. The technologies can also decision-make, as well as interact with humans.
In The New Physics of Financial Services, potentially the largest study of its kind, the 200 subject matter experts from globally established incumbents, fintechs and government agree that:
When it comes to the complexities of ethics and society, it was also agreed, that whether AI is a force for good in industry and society, will largely depend on the choices leaders make.
A great place to start is the people impact. In Sydney, according to the last Census, the financial services sector employs approximately 17% of the working population, a very important part of Australia’s largest economy. As AI changes the way jobs are constructed, through for example, augmenting human work with cognitive assistants, there will be a significant impact on large segments of the workforce.
An example of AI augmentation is a recommendation engine that supports a contact centre agent in conversation with a customer by providing information about the customer’s history, and combining it with experience gleaned from the data from many customers. This enables the agent to offer knowledge-based, targeted recommendations to the customer.
As AI creates more service efficiency and effectiveness throughout the value chain, the question will be whether financial institutions choose to ‘harvest’ the capacity for cost savings, or re-invest it into other value creating and effective activities such as new services.
Whatever happens, organisations will need to redefine work and create good jobs for people. Those impacted staff will require new combinations of skills to be relevant to the changing world. The competition for valuable human skills such as creative thinking, sense making, new and adaptive thinking, and cultural understanding will become more intense. In the short term, there is likely to be negative consequences for those whose strengths lie elsewhere.
We think that as part of the ethical and moral considerations associated with AI, institutions and their leaders need to consider the broader implications for AI on society, and take an active role in addressing both these opportunities and risks.
Every pathway will be different, but we think AI leaders will need to take four critical steps:
Efforts to reskill need a clear perspective on the roles and responsibilities that institutions need today, and an understanding of how the demand for skills will change over time. This is not easy to determine and a lack of vision and coordinated strategy is likely to put the institution at risk of a skills deficit.
To counter this risk Deloitte has developed a machine learning driven platform to predict the impact of cognitive technology (and other strategies) on the future workforce. The model analyses the attributes of the work financial services organisations do, and the people who do it, and lets us specify how, and when, each job will be impacted. It also assists us to determine how talent can be re-skilled to address potential gaps. We have found this to be very useful and its insights are in high demand from boards and executives.
Our modelling shows that organisational skill shortages are not as dire as some suggest. We believe that many large organisations could actively minimise negative impacts by better understanding the skills they really have, and target learning, exposure and job redesign strategies where they will add most value.
So once we identify that talent, how do we unlock its value?
Talent strategies need to enable the AI strategy and business vision and be underpinned by operating model and organisational culture changes. This can be difficult. For example, even when an organisation can see the potential of mobility to strengthen its workforce capability, the existing hierarchy is a significant barrier to change. Managers tend to want to ‘own’ talented staff. They are loathe to ‘let them go’ in case they fail to meet their own short term performance goals. A longerterm talent mobility strategy needs to incentivise managers to do the right thing by the organisation and its people.
Leaders also need to invest the time to establish a baseline understanding of AI among the team, explore its possibilities, and continue to engage them in an inclusive way throughout the journey. We have found that a focus on the potential applications and benefits of AI, rather than the technology, can be an effective way of establishing organisational momentum behind AI programs.
Addressing the potential of AI, and dealing with the array of risks related to the safety of the financial system and protection of staff members and customers, will require an extensive network of partnerships between institutions, regulators and the broader public. Organisations will need to balance the opportunities and risks associated with change. Responding to these opportunities and challenges will demand real leadership from the sector, and a willingness to shape the economic and social agenda in equal measure. The winners will do both really well.
This article was first published in Asia-Pacific Banking & Finance.
Michael works with Financial Services industry clients in all areas of Human Capital. He has worked extensively in the Asia Pacific and European regions. His areas of expertise include Business Transformation, Organisation Design and Workforce Transition, Change Management, HR Transformation, Finance Transformation, Cost Reduction and Post Merger Integration.