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The challenges of implementing AI
To help finance teams considering artificial intelligence or cognitive computing technologies, ICAEW and Deloitte have identified the common barriers to success that must be overcome. These include: access to data, availability of skills and the integration of systems.
Data volumes and quality are crucial to the success of AI systems. Without enough good data, computer models will not be able to learn, and acquiring and labelling data retrospectively can be time consuming and costly.
Transactional accounting data is well-structured and high quality, and should be a promising starting point for developing models. However, given long-standing issues around data in many organisations, especially those with complex and unintegrated legacy systems, this is still likely to be a major challenge in practice.