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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.
Setting a clear vision for autonomous finance that uses advanced analytics capabilities to achieve strategic financial outcomesWorkforce planning to identify talent needs and ensure the right mix of skillsCreating analytics centers of excellence to build specialized domain expertise Seeking out and rewarding competencies for innovation, risk taking and iteration in applying AI to finance processesLow 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.
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 and will remain relevant even when digital technologies change.
Changing perceptions from the outside-in to ensure top AI talent can experience a strong sense of belonging within the finance functionDespite 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:Finance will acquire talent with expectations that finance can’t meet.