A.I. may even sniff out new types of chicanery, said Tom Gira, executive vice president for market regulation at the Financial Industry Regulatory Authority (FINRA).

"The biggest concern we have is that there is some manipulative scheme that we are not even aware of," he told Reuters. "It seems like these tools have the potential to give us a better window into the market for those types of scenarios."

FINRA plans to test artificial intelligence software being developed in-house for surveillance next year, while Nasdaq Inc (NDAQ.O) and the London Stock Exchange Group (LSE.L) expect to use it by year-end.

The exchange operators also plan to sell the technology to banks and fund managers, so that they can monitor their traders.

Artificial intelligence is the notion that computers can imitate nuanced human behavior, like understanding language, solving puzzles or even diagnosing diseases. It has been in development since the 1950s and is now used in some mainstream ways, like Siri, an application on Apple Inc's (AAPL.O) iPhone that can engage in conversation and perform tasks. 

Eoin Treacy's view

Artificial Intelligence (AI) is a great example of the exponential growth curve described by Ray Kurzweil. It has been in development since the 1950s but had an inconsequential impact on the wider economy. When the digital economy really took off it provided the feedstock for AI to be truly useful and advances in computing, to make sense of the flood of data, were equally important. 

This chart from Gartner’s hype cycle illustrates their view that Machine Learning is at the peak of inflated expectations but that a significant number of additional artificial intelligence vectors are still on the ascendency. At the EmTech conference at MIT last week a third of speakers focused on artificial intelligence and the major sponsor of the event (Rage Frameworks) 

If we are indeed at the top of the hype cycle it is important to identify what AI systems are good at and what is still too much to ask. AI is good at finding patterns in large amounts of data. Parsing the conclusions to come up with actionable information is much more challenging and requires intimate knowledge of the business.  

They are getting better all the time but when I see a panel discussion with management consultants from three different firms telling me how great something is I tend to get suspicious. Perhaps the best way to think about AI’s utility is to focus on specific tasks that it can be applied to; preferably repetitive in nature. I think it is still too early to give very much credence to any talk of general AI where programs can be let loose on data, free to come up with their own conclusions. 

LSE has been ranging in a volatile manner for two years but is testing the upper side at present and a sustained move below 2700p would be required to question potential for additional upside. 

Nasdaq remains in a consistent medium-term uptrend and is now testing the region of the trend mean where it has found support on multiple previous occasions. A sustained move below $65 would be required to begin to question medium-term scope for continued upside.