The Growing use of artificial intelligence tools by businesses was the focal point of data analytics and data management trends predicted by a group of IT consultants and vendor execs.
GRANTS PASS, Ore. Business uses of AI analytics and data applications will grow over the couple of months.
Those were among the predictions made at the 2017 Pacific Northwest BI & Analytics Summit, which brought together a group of IT consultants and vendor executives here this month to discuss and forecast business intelligence, advanced data analytics and data management trends.
Other topics they looked at icludes edge analytics and new data privacy rules taking effect in the European Union next year. But artificial intelligence (AI) was top of mind during the predictions part of the proceedings.
Organizations progressively will find that the different pools of big data they’re collecting can’t be effectively analyzed with traditional tools and human brainpower, said Yves de Montcheuil, a France-based consultant who works with technology startups on marketing and strategy.
As a result, he thinks AI software will become more and more crucial to getting real business value from big data applications.
“AI is becoming the new black,” de Montcheuil said — a statement amended shortly thereafter by IBM executive Harriet Fryman, who proclaimed AI to be “the new bacon.”
More To Think About On Artificial Intelligence Data Management
But, as AI analytics becomes more common in corporate enterprises, managing the process is expected to get more important and more complex.
Analytics teams will have to pay more attention to “the composition of AI systems,” said Donald Farmer, principal of consultancy TreeHive Strategy in Woodinville, Wash.
They’ll likewise need to actualize definite administration and oversight systems “as companies begin to set up a large number of data alogrithms,” chimed in Shawn Rogers, senior executive analytic strategy at vendor Tibco Software Inc.
Gartner analyst Merv Adrian predicts that networks of AI-powered tools and devices that can communicate with one another and have the ability to ingest data on their own developments Farmer said would make it more clear that data scientists and other data analysts are “participants in AI systems” as opposed to users of the technology in a traditional sense.
Another issue to contend with is the level of uncertainty in what AI data algorithms predict. Farmer said AI-based analytical models tend to be accurate if they’re well designed, but there’s almost never a 100% probability that their findings it correctly, Something that needs to be made clear to business executives so they don’t expect infallibility from the technology. “If we’re going to live in a world where things are going to be driven by algorithms, we have to be able to convey their ambiguity,” he said.
Edge Data Analytics Set To Take Off?
In addition to increased use of AI analytics, big data environments are likely to push deployments of “in-flight” data analytics applications at the edge of corporate networks, said Mike Ferguson, managing director of U.K.-based consultancy Intelligent Business Strategies Ltd.
As data continuously streams from devices on the internet of things (IoT), smartphone apps, stock-trading systems and the like, trying to funnel it all into a centralized data repository for processing and data analysis becomes a tall order, Ferguson said.
He envisions wider development of event-driven data architectures with edge analytics systems that can trigger automated actions on the fly. “This is a world where the data never stops, and it’s completely challenging the way we’ve done things in the past,” he noted.
Companies face a different kind of challenge in complying with the EU’s General Data Protection Regulation (GDPR), which establishes stricter rules on data privacy and security for companies that operate in Europe or do business with organizations that handle the personal data of EU residents.
Due to become law in May 2018, the GDPR will require new data governance processes in many companies a step that Farmer said could end up contributing to the law’s undoing because of the potential for added business costs. “The GDPR could collapse,” he said. “The way it forces you to change how you do business will be unacceptable [to a lot of organizations].”
If the law doesn’t fall apart, EU regulators likely will find it hard to broadly enforce the new rules because of the large number of companies that are affected, Adrian said. But IT and business executives shouldn’t get complacent about their GDPR compliance efforts, he cautioned, saying that he expects EU officials to try to “make an example of someone” to scare other organizations into adhering to the rules.
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