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Readiness of Finance Department for the Adoption of Automation and AI

According to a report by Paro, there remains a significant gap in adoption of artificial intelligence (AI) and machine learning (ML) within finance. While 83% of surveyed executives say adopting AI is important, almost half of businesses have yet to do so.

The top barriers to adoption cited include:

  • Lack of proficiency in advanced analytics, data governance, and technology

  • Concerns about security and the loss of human judgement or oversight

  • Lack of trust in data

  • Difficulty translating data into insights

Among the adopters, the top AI use cases are:

  1. Predictive analytics and forecasting for sales, marketing, etc. (67%)

  2. Process automation for internal workflows (56%)

  3. Personalization, e.g., tailored recommendations for customers (54%)

And if you are looking to adopt automation and AI within your finance department, consider the readiness of the respective areas. For example, financial reporting, accounts receivables (AR) and accounts payable (AP) are fairly mature areas which are ripe for digital transformation.

If you are interested to learn more, check out our case study on how Owndays, a fast-growing Japanese eyewear retailer, slashed 40 hours of data entry work every week with RPA.


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