In a recent article in HBR, AI and machine learning was described as the most important general-purpose technology of our era. According to Forrester, investment in the technology will increase more than 300% in 2017 compared with 2016, while Gartner has put AI at the top of its new ‘Top 10 Strategic Technology Trends for 2017’ report. As Amazon chief Jeff Bezos told the Internet Association’s annual gala in Washington DC, ‘It is a renaissance, it is a golden age. We are now solving problems with machine learning and artificial intelligence that were in the realm of science fiction for the last several decades. And natural language understanding, machine vision problems, it really is an amazing renaissance.’
One of the primary ways in which AI is having an impact is in driving business intelligence. Machine learning algorithms can essentially do much of the work traditionally done by human analysts, identifying patterns in the data and answering questions, which is now impossible because of the sheer scale of the data companies hold.
Uri Maoz is the Head of Product and Business Development for Anodot, based in San Francisco, California. Uri has over 15 years of experience in the Software Industry, in which he led Product Management, R&D, and Business Development. He was in charge of the development and implementation of several Analytics and Machine Learning products. He will discuss how AI is being used by businesses at Business Intelligence Innovation Summit, which takes place this November 14-15 at the Hilton Chicago. We sat down with him ahead of his presentation.
What impact do you see AI having on analytics?
With the massive amounts of data being generated by businesses, important details get lost in averages when trying to analyze manually. Users are forced to make hypotheses and then dig into the data to see if it fits their hypothesis. AI works differently. AI asks all the possible questions for you and then highlights where you need to look, the specific places where there was unusual behavior - for example, a great business opportunity or a glitch. This allows companies to quickly detect the business incidents that matter, and prevent or remedy urgent problems quickly, so they never will experience another revenue leak or brand-damaging incident.
How do you see the wider data landscape changing in the next 5 years?
We see data becoming more of a core competency within companies, with full-fledged departments devoted to it. These are made up of a chief data officer and a team handling data ops and another team managing data quality. The change is gaining momentum, and we believe that in the next 5 years every company with more than 500 employees will have these functions. The ability to turn data into insights gives companies a competitive advantage, and the sooner they advance to this, the sooner they will see the fruits of this important business advantage. We also see access to data becoming democratized within companies, with greater access within companies to core datasets and having the analytical capabilities at their fingertips so they do not need to run to a BI specialist for every report.
Anodot look at real-time analytics, what is the biggest challenge you see in this area?
There are many technological challenges in providing real-time AI-powered analytics. Most of the standard AI algorithms are not designed to work at the massive scale required by Big Data. If you try to run many of the typical AI algorithms learned in University on Big Data, you will find that they may work, but the computing power they require is astronomical, or the processing time is far too long to wait in a business environment. These algorithms are fine in the academic arena, and for testing. But when you are dealing with millions of metrics that are updating every minute, you need something that can work at scale. As a result, at Anodot, we have adapted the well-known algorithms and created many of our own, with patented processes involved.
Uses for the IoT are increasing every day, how do you see this developing in the coming years?
We expect increases in IoT in the consumer realm, with home bots and personal devices like exercise bracelets, or home medical kits. Also on the B2B side we expect a major increase in manufacturing usage of IOT to track what is happening with their machinery on the factory floor. Using AI in conjunction with sensor data from machinery, a factory manager can identify which machines need preventative maintenance. A breakdown on the factory floor can disable an entire production line for days, while waiting for a replacement part to be flown in; so preemptive maintenance reduced this significant downtime, saving millions of dollars.
What can our audience expect to take away from your presentation?
You will hear from one of the leading Web Brands, Credit Karma, how they use AI analytics to gain crucial insights into their business.
You can hear more from Uri, as well as other industry leaders, at the Business Intelligence Innovation Summit. To view the full line-up of speakers, click here.