- Starting with Data and SQL: Tax professionals should focus on understanding data as the foundation for engaging with AI, using SQL to ask precise questions about transactional data. This approach shifts their mindset from relying on static reports to directly interacting with data, enhancing their control over tax-related issues.
- Developing an Engineering Mindset: Before diving into coding, professionals can cultivate an engineering mindset by experimenting with no-code AI tools. This helps them understand the behavior and limitations of AI systems, which is crucial for making informed decisions in the tax field where accuracy is paramount.
- Learning to Build and Implement: Mastering programming languages like Python allows tax professionals to manipulate data more effectively than spreadsheets and enables them to build scalable solutions. A fundamental understanding of AI principles is essential to assess risks and implement tax logic reliably, ensuring that they remain relevant as the profession evolves. Regular, incremental learning through building systems will lead to deeper understanding and adaptation in the changing landscape of tax work.
Source Aleksandra Bal
Latest Posts in "World"
- E–invoicing Developments Tracker
- OECD Releases Guidance on Digital Transactional Reporting Systems for VAT Compliance and Administration
- OECD Issues Guidance on Digital VAT Transaction Reporting to Promote Global Standardisation and Compliance
- OECD Releases Guidance on Digital Continuous Transactional Reporting for VAT: Policy and Design Considerations
- OECD Issues Guidance on Digital Continuous Transactional Reporting Regimes for VAT Compliance and Administration
