A Future-Forward Talent Guide for Finance

In the quest to acquire digital finance talent, AI poses the greatest opportunity for which finance is least prepared.

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Finding and retaining top finance talent in the AI generation

AI has the potential to supercharge everything — from error detection to forecasting and predictive analytics. Eighty percent of CFOs will spend more on AI in the next two years — but attracting, developing and retaining AI talent requires a plan. 

Download this guide to learn:

  • What traits and roles comprise the AI generation

  • How to attract and recruit AI talent effectively

  • How to manage, develop and retain this unique talent pool

Three key actions CFOs can take to build and nurture a future-ready finance team

Finance leaders see a future for finance that is digital, scalable and data-rich. CFOs must redefine the digital function to attract and retain the next generation of finance talent.

Lay the foundation for autonomous finance.

CFOs have ambitious plans for realizing the vision of autonomous finance — an AI-powered finance function that delivers data on demand, has a highly scalable structure, is digital by default and can solve a high concentration of complex problems. 

To support the vision, CFOs are evolving their organizations’ team structures, roles, skills and leadership capabilities to create a place where AI and digital talent can thrive. Through 2025, 40% of finance roles will be either new or significantly reshaped due to finance technology. 

How will the finance talent evolution play out?

With 73% of finance leaders expecting to boost AI staffing through 2025, the demand for AI talent will increase — along with pay expectations and time to hire. CFOs looking to get ahead of this demand will become heavily involved in developing digital skills in their teams, expanding their finance IT capabilities and improving financial data literacy.

As AI solutions and staffing increase, so will efficiency. This opens new opportunities for finance to contribute to business strategy beyond data reporting and compliance. On the accounting side, AI models are already reducing reconciliation time, increasing error detection and reducing time to close. In financial analysis, leading companies are using AI to execute cash-flow forecasts to generate better liquidity and profitability analysis. Developments like these will increasingly allow finance teams to shift time to more specialized aspects of their jobs, leaving the routine tasks to automated systems. 

The challenge? Talent is scarce. Two out of three finance leaders agree the digital skills gap is growing — and our research supports their observation. Out of a pool of ~140,000 data science resumes, only 3,000 met the criteria for “superstar AI talent.” 

How do leading companies fulfill the vision of autonomous finance?

Inflation and labor shortages may pressure CFOs to justify their reliance on labor-based models, but technology spending offers much more reliable, efficient scalability. CFOs can position their organizations for success by:

  • Setting a clear vision for autonomous finance that uses advanced analytics capabilities to achieve strategic financial outcomes

  • Upskilling their finance teams for digital through:

    • Workforce planning to identify talent needs and ensure the right mix of skills

    • Incremental staffing that balances technical expertise with business interpretation expertise

    • Creating analytics centers of excellence to build specialized domain expertise

    • Enabling the team to trust the technologies by exploring algorithmic decision making and creating necessary guardrails

    • Infusing the organization with project management expertise to enable a successful transformation

  • Breaking down established functions that no longer serve operational goals — and building or elevating new subfunctions that do

  • Providing agile access to talent from throughout the finance function to tackle ongoing digital skills scarcities

  • Seeking out and rewarding competencies for innovation, risk taking and iteration in applying AI to finance processes

Set up the finance team for digital success.

Low digital proficiency keeps finance teams from harnessing the potential of autonomous finance — yet only 19% of finance leaders are satisfied with the relevance of digital upskilling learning and development within their organizations. 

Finance can equip teams to work more efficiently and generate higher quality insights in less time by investing in digital skills. The ability to exploit technologies, such as RPA, ML and NLP, rests on five core competencies:

  • Technological literacy: The ability to exploit digital technology to drive better outcomes for finance and the business

  • Digital translation: The ability to explain how digital technologies interact with finance stakeholders, processes and systems

  • Digital learning and development: The ability to fast-cycle new digital learning requirements within the new learning environment

  • Digital bias management: The ability to understand and articulate bias in ML and manage the risk

  • Digital ambition: The ability and motivation to embrace technology and new ways of working

A deep analysis of these five competencies across finance disciplines, including 300 activities and their associated tasks, revealed a total of 75 components (categorized as skills, knowledge and/or abilities) that are needed to perform those tasks. 

A common belief among finance leaders is that proficiency in core digital competencies requires extensive technology-based skills, knowledge and abilities. With 64% of finance leaders believing their teams are not effective at using digital technologies, only 23% of finance leaders rate their teams as proficient at these five digital competencies.  

The good news? Only 25% of the digital competency components are technology-based. The rest are classified as data-, finance- or sociocreative-based capabilities.

Most of the capabilities that form finance’s digital competencies are already familiar to finance teams, are scalable across multiple digital technologies (including RPA, ML and NLP), and will remain relevant even when digital technologies change. 

Successful CFOs build their teams’ digital competency proficiency by educating finance staff on the five competencies and their underlying components, setting the expectation that people managers will continue to reinforce the competencies with their direct reports through their development plans and to provide coaching where appropriate, and asking finance leaders to provide team-specific examples of how these five competencies look in various parts of the finance organization.

Create an organization where digital and AI talent can flourish.

Whether upskilling existing staff or recruiting new staff, CFOs must radically rethink the finance employee value proposition and work culture to attract and retain top digital talent. For finance leaders, this process includes two challenges:

  1. Working from the inside-out to ensure that leadership’s mindsets and assumptions about digital finance talent’s work and career preferences are accurate — and adjusting management approaches accordingly

  2. Changing perceptions from the outside-in to ensure top AI talent can experience a strong sense of belonging within the finance function

Clarify assumptions about digital talent.

Despite the growing proportion of digital talent within the finance function, CFOs may carry old assumptions about this talent’s work preferences. Talent decisions made on false assumptions can affect finance in two ways:

  1. Finance’s talent strategy won’t align with team members’ aspirations, resulting in alienation.

  2. Finance will acquire talent with expectations that finance can’t meet.

Both of these scenarios lead to attrition of digital finance talent, which is already a concern for CFOs.

Which assumptions about digital finance talent are valid — and which warrant a second look?

We surveyed hundreds of digital and core finance professionals on their work preferences, aspirations, beliefs and goals. Some of the takeaways:

  • Digital finance talent goes above and beyond in their daily work. This effort adds value to the finance organization and creates opportunities for digital finance talent to take on new responsibility and grow. It also begs the question: How much work is too much? CFOs can nurture top talent by supporting work-life balance to help avoid burnout. (Gartner clients can find further insights in our research, How CFOs Can Structure Project Planning to Improve Digital Finance Talent’s Work-Life Balance.)

  • Digital finance talent likes to work on their own time. Nearly two-thirds of digital finance talent say they do at least 20% of their work outside of normal working hours. Successful CFOs see the benefits of offering flexible hours — including better engagement and productivity — as well as the potential side effects, such as reduced collaboration.

  • Digital finance talent likes to work with others. Less than one-third of digital finance talent agree they can accomplish things at work by themselves. This opens the door to increased productivity by pairing up digital and core finance talent.

  • Digital finance talent either feels passionate about finance — or is open to finding their passion in finance. Nearly three-fourths of digital finance talent either disagreed or expressed a neutral view that their career passion lies outside the finance function. This bodes well for CFOs who take steps to understand and accommodate digital finance talent’s career aspirations within finance.

A note on nurturing AI talent: Finding the right data science talent is critical to building an AI-powered finance organization. CFOs should take a “build it and they will come” approach — creating an organization characterized by modern analytics tools, high-quality data, meaningful learning opportunities and clear career pathing. 

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AI has a multitude of applications across the finance function, bringing increased accuracy and efficiency to typical finance activities. Some examples of how AI is used in finance include: planning and forecasting, anomaly and error detection, process automation, compliance and risk monitoring, and more.

Advancements in AI are powering the vision of autonomous finance, in which processes and activities are partly governed and majority operated by self-learning software agents that optimize front-, middle- and back-office operations. As AI solutions and staffing increase, so will efficiency. This opens new opportunities for finance to contribute to business strategy beyond data reporting and compliance.

The future of digital finance will rest on finance teams’ ability to exploit technologies, such as RPA, ML and NLP. Digital finance teams will need to build skills in five core competency areas: technological literacy, digital translation, digital learning and development, digital bias management and digital ambition. Most of the capabilities that form these digital competencies are already familiar to finance teams.

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