In the world of business, the implementation of artificial intelligence (AI) is seen as a game-changer. However, a recent report has shed light on the main issues that companies need to address in order to successfully integrate AI into their operations.

One of the major challenges identified in the report is legacy system integration. Many companies struggle to incorporate AI into their existing systems, leading to fragmented data and limited internal expertise. This, in turn, hinders the effective implementation of AI technology.

Another issue highlighted in the report is the fragmented nature of data within companies. This not only impacts data governance frameworks but also creates obstacles for AI deployments. The complexity of data estates in many companies is cited as a major reason for the constraints faced in the sector.

The report reveals that firms surveyed manage an average of 17 data sources, with many citing this as a significant issue. This challenge is further exacerbated after mergers and acquisitions, making data integration even more complex.

Despite these challenges, the authors of the report believe that AI has the potential to positively impact costs and scalability for companies. By addressing issues such as manual error correction and mistakes in reconciliation processes, AI could streamline operations and improve efficiency.

The report suggests that decision-makers focus on reconciliation processes as an initial testing ground for AI. This domain is rule-based and lends itself well to automation, offering quick and tangible results.

However, it is important to note that implementing any form of automation on a fragmented architecture and fractured data layer may not be without its challenges. The report emphasizes the importance of structuring fragmented data sources and recommends considering cloud-based AI platforms as a solution.