Companies have high hopes for transformational technologies, especially those that leverage the vast amount of data being collected. Approaches using methods such as artificial intelligence (AI), machine learning (ML) and deep learning are becoming increasingly accessible and gaining significant traction, as they allow for deep insights to be extracted from large and varied data sets. As noted in the 2019 IT Audit survey by Protiviti and ISACA, this transformation has the potential to fuel long-term growth. However, as Protiviti's recent global AI survey reveals, most companies are still at the starting gate when it comes to figuring out the answers to basic questions: What are the possible use cases for AI? Can we measure ROI? What data do we have and how usable is it?

Like any algorithm- and data-driven process, artificial intelligence (AI) presents internal audit with a clear role in ensuring accuracy and reliability. It is important that boards and other stakeholders understand stages in the AI life cycle where internal audit's focus can provide positive effect. How can the board best support the CAE's efforts to ensure that the internal audit team is prepared to provide assurance over AI and capitalize on its efficiencies in appropriate audit plans and activities? Download the new issue and share it with your audit committee. To what extent does you internal audit function incorporate AI in its activities?

Internal audit can play a key part in identifying and defending against risks from emerging technology such as the internet of things, and it also can aid in identifying opportunities such as how IoT can be used in sales distribution and inventory control, Jose Tabuena writes. Internal audit will face challenges, however, in keeping up with the rapid advancement of IoT and the resulting disruption, Tabuena writes.