Firms that keep pace with machine learning will forge a brighter path to innovation and success, rather than playing catch-up later. Picture a world where your machines have the ability to detect exactly who you are through facial recognition, pinpoint what your next purchases will be via product recommendations and your navigation systems pick-up traffic congestions in real-time. These are only a handful of the outcomes shaped by machine learning (ML). Below I'll dive deeper into the impacts of ML and it's tremendous potential to transform the enterprise. Machine learning is a subset of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience – much the same way humans do.

Manual checking of expense claims and other business expenditure is too time-consuming to be effective in spotting issues. The advent of artificial intelligence is a cause of widespread concern in the industrial world. A key issue, of course, is the effect on employment, and there are wide-ranging discussions of whether the administrative-type jobs that are likely to be lost to AI will be made up for by the creation of new roles or whether there will be large-scale unemployment. But there are other areas that businesses need to consider before launching themselves into this brave new world - as is made clear in a report, Making AI Responsible - and Effective, which was published by the international business consultancy Cognizant earlier this month. Having said that, businesses can make huge gains by applying AI to certain parts of their operations.

Artificial intelligence is impacting all kind of industries and accounting is no exception. The growth of automated solutions particularly in various finance functions – primarily led to anxiety among financial professionals that their positions might be replaced by machines. With automation becoming more ordinary, however, it's clear that accountants are still needed in the endeavor. Some accounting practices are starting to employ such advanced technology to simplify their operations. The general result that they are perceiving is saving time, reducing costs, increasing productivity and providing better accuracy.

Consider the following expenses claims: registration fees for a cancelled seminar, two separate claims for mileage when the employees travelled together, and a sandwich-and-coffee dinner claimed as the full per diem. While it's easy to believe that a few dishonest claims won't hurt, for individual victims, expenses fraud can be costly. Research conducted by the National Fraud Authority suggests that exaggerated expenses claims cost the British economy around 100 million annually; the private sector alone lost 80 million in 2013. Imagine if 20 per cent of your staff added 10 per cent to each mileage claim; the cumulative loss for the company would quickly become significant. Existing fraud detection systems flag dubious-looking expenses according to a set of rules, such as challenging claims in excess of a fixed cash amount or those that are 5 percent higher than claims submitted by peers in similar positions.