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Survey respondents see great promise in automation, but expect short-term disruption as they implement these technologies. Nowhere is this disruption more apparent than in the area of talent. As tasks once performed by humans are increasingly performed by machines, required skills will differ in fundamental ways from those of the past. In addition to traditional finance competencies, future finance teams will require process management and exception management skills to administer digitally enabled processes, and digital finance experts and data scientists to analyse internal and external data to provide critical insights to the business.

This has profound implications for the ways finance organisations must source and develop these skills. Complicating matters further, respondents indicate that the rapidly changing technology landscape makes it difficult to predict precisely what skills will be needed in the future. In fact, respondents cannot agree on whether intelligent automation will create or eliminate jobs in the finance function.

Impact of AI on talent pool

There is strong consensus among survey respondents that the overall impact of automation on their talent pool will be positive, liberating staff from spending time on manual processes, and freeing them to focus on higher value-added activities: more than three-quarters of organisations expect automation to free staff to undertake more value-added work.

Fully enjoying the benefits of automating manual processes, however, will require having finance staff with the skills to take on new roles. The finance workforce of the future will place a premium on broad ‘enabling’ skills that can adapt to a changing business environment rather than more narrow task-specific skills. Some of the skills include:

  • Data utilisation and technology, including data modelling and visualisation, strategic trend analysis, design thinking, and programming.
  • Behavioural, including strategic thinking, service management, relationship management, and communications.
  • Finance technical, including business modelling, process design, and financial driver analysis.
     
Quote by Nikki McAllen

Needless to say, most of these skills are in short supply and high demand, as the educational programs offered by universities and other accounting continue to focus largely on standards, rules, and technical skills rather than the more collaborative, business-focused skills needed in the future.

A majority of organisations expect between 11 and 20 percent of their finance workforce to have their jobs redefined or eliminated in the next two years as a result of automation, with overall expectations that a little more than half of staff impacted by automation will be retained/reskilled and the rest made redundant.

While admirable in intent, the expectations that such a high proportion of finance staff can be retrained may be overly optimistic. Although most every organisation will have a group of high-potential employees it can develop, next generation skills will often be in short supply among existing staff, especially those currently working in the transaction-oriented process that are some of the most immediate candidates for automation.

Impact of AI on workforce

Comparing the outlook of high-performing organisations1 and others on how automation will impact their talents pools reveals important differences in both expectations and approach. First, high-performing companies expect a much greater percentage of their staff to be impacted by automation. As these companies tend to be ahead of the curve in implementing these technologies, it stands to reason that more of their staff will be impacted by them in the short- to medium-term. However, they also expect to retrain/retain a higher percent of staff impacted by automation. This may not only reflect high-performing companies having more sophisticated training and development programs, but also more highly skilled employees who are better able to transition from transaction-oriented roles to those with more analytical responsibilities.

Impact of AI on workforce
Quote by Andrew Harding

Key actions: Talent in the age of automation

Build, buy and borrow’ talent through flexible staffing models. The skills needed in the next-generation workforce are in high demand and short supply. Reskilling existing staff and hiring new staff will often prove insufficient to provide access to the required skills. Organisations should look to multiple sources to acquire them. The use of partnerships, contingent workers and managed services, for example, can all help relieve the burden to source skills internally.

Be realistic about the extent to which existing staff can be retrained/retained. Loyalty to existing staff and a desire to retain organisation-specific knowledge often leads to a strong organisational bias towards retraining rather than making redundant staff impacted by automation. This staff, however, tends to be heavily concentrated in transaction-based roles, and retraining them to take on roles with more strategic responsibilities can often prove difficult. Few accounts payables clerks, for example, have the capability to evolve into business analysts.

Plan ahead for scarce skill sets. Rather than reactively hiring for new skills, for example those needed for a specific technology implementation, anticipate how the workforce must evolve over time and proactively identify and hire for needed future skill sets. As the precise skills needed may be difficult to predict, focus on high-level ‘enabling’ skills that are valuable in a variety of environments.

Take a portfolio view of skills management, utilising cross-functional teams. Successfully executing on future finance initiatives requires staff with a variety of skills, some of them highly specialised. These skills will seldom all reside in the same person. To contend with this reality, create teams incorporating individuals with specialised technology, analytics and functional expertise. Rotational programs that place finance staff in other business functions can also help broaden staff skill sets.

Footnote

  1. High-performing organisations are defined as ranking in the top 16 percent on a combined measure of revenue and profitability growth

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View the Finance Survey infographic (PDF 97 KB).