The buy side is not buying into artificial intelligence or machine learning, or at least for the moment.

Of the 60 buy-side firms interviewed by industry analysis firm Tabb Group for the research study on front office automation, 56% of them state that they had no plans to implement cognitive technologies as any part of their trade workflow.

Only 7% of the respondents replied that they already employ cognitive technologies while 19% are exploring its use and another 18% say they are interested but lack the technical resources.

“The 7% figure was pretty evenly spread across the different tiers of firms, Dayle Scher, a senior analyst at the Tabb Group and the author of Automating the Front Office: Active Management 2.0, told Markets Media.

“What is surprising– and contrary to many of the results of this study– 69% of mutual fund companies have no plans to do so either,” she wrote in the research note.

However, mutual funds (15%) lead the pack regarding their adoption of the technology at approximately twice the rate of hedge funds (8%) and five times that of long-only funds (3%).

The trend is almost counterintuitive, according to John Adam, senior director, portfolio management & trading at FactSet and whose firm is distributing the report.

“I think that hedge funds are a bit more conservative on trade automation because often they are pursuing strategies that do not necessarily fit well to algorithms that are created for the long-onlys in the market,” he said.

A significant issue gating the buy side’s adoption of the technology is setting reasonable expectations while filtering the claims of what AI can achieve from what it can deliver.

“Certainly there are broker algorithms that claim that their algorithms are intelligent or adaptive,” said Adams. “Here is where the marketing terms mix with the science.”

While the front office continues to examine AI and machine learning, the technologies are establishing stronger toeholds in the asset manager’s middle office.

“It’s moving into the compliance domain, specifically in trade surveillance: natural language processing using machine learning to monitor e-communications and voice communications and in AML/KYC screening,” wrote Scher.

“In terms of cognitive technologies, and technologies similar to it, we are really still on the leading edge,” added Adams noting that the industry is still in its early days of adopting cognitive technologies.