Can you imagine taking a cab which is driverless or conducting all basic banking transactions with the help of ATM without requiring a teller. Let’s go one step further, your medical treatment being done by a robot or robots teaching you in the classrooms. Well, all of this is not a dream anymore but possible and achievable because of Artificial Intelligence.
Artificial Intelligence, though in a nascent stage, has already started to enter a lot of fields and is trying to make a mark. AI has already started to automate some type of jobs and it’s not far when AI will replace all the repetitive type of jobs in the analytics space and perform it solely without any human intervention.
Neerav Parekh, Founder and Director vPhrase, comments “There are two kinds of analytics jobs, one which involves exploratory analytics and the other repetitive analytics. Let me explain with examples. If you are given a full dump of traffic data of a website and asked to figure out interesting insights which can help the business increase conversions, I would classify that as exploratory kind of work whereas if you are asked to prepare your weekly digital marketing reports from the traffic data, I would call it repetitive analytics work. Current AI based technologies are already automating the repetitive kind of work. However, they are not yet evolved to an extent where they can take up exploratory work. Hence, if you are doing repetitive kind of analytics work, you better upgrade your skills and start doing more challenging work, as you have your job only till someone like us comes knocking to your company door.”
Also as the technology develops and more research in AI is carried out, the advancements may result in replacement of other types of analytic jobs which require thinking and interpreting and taking decisions.
An excellent example is of Google’s AlphaGo program. It competed and won four out of five matches against champion Lee Sedol in the Chinese board game Go. This victory is definitely seen as a milestone by the AI industry particularly because of the complexity of the game. Though this is just the tip of iceberg, AI can go places.
Nitin Babel, Co-Founder Niki. ai comments, “Yes. Down the line, AI will be able to perform the analytics work as we know today. In the past, we have seen numerous tools that came up and automated much of the things in analytics. The next phase, we believe, will be of Cognitive Automation. With AI, softwares will be able to perform cognitively complex tasks, tasks that require creativity, original thinking and free association (Example: Baidu AI recently created music of its own by analysing paintings). However, this does not mean that analytics will get completely possessed by AI. Earlier, analytical tools led analysts go a long way in saving time. Now, with AI as an aid, analysts will have a chance to enhance further, get more innovative and meaningful.”
“There is migration of work from the current analytics platforms to new AI driven platforms, especially in the space of real-time feedback and actions. I expect this to happen in the next 4-5 years as more and more resources such as IBM Watson become mainstream.” says Rajesh Krishnamoorthy, IT Head Cambridge Technology Enterprises’ “Areas such as Sensor Management, Smart City Management, Routing, Remote Health Care and Alerting would be entirely managed by Artificial Intelligence (AI) based platforms with humans providing input directions and reactions rather than making actual decisions in a certain situation. One of the vital areas is cyber-security which I think will be dominated by AI. The current threat surfaces are huge and cannot be monitored by human hands alone.”
But to what extent can Artificial Intelligence replace humans and take up their jobs or perform independently without any human help is a big question. And apart from analytics which other industries face the same threat?
As per Atul Rai, CEO and Co-Founder Staqu Technologies “ It’s just not analytics but every domain which does product reparative pattern in its data can be replaced by AI, A number of predictions have been made that say that after 2030, almost all of the white collar jobs that include, but are not limited to, diagnosing illness (medicine), software development (technology), filing a patent (law), teaching an entry level course (education), and even financial analysis (fintech) and trend analysis (e-commerce) will be automated by AI. The interesting part about this robust AI technology is that it doesn’t even need to have domain expertise to do the jobs. All it requires is data and we have more than enough of it!”
According to Aindra Systems, one of India’s leading AI startup, “Yes, very soon Analytics jobs will be taken over by AI. In fact most of the Analytics work is already getting automated increasingly. We think the fields that will be affected by AI thus are those that only needs to process data. This will include all data analysis jobs including those of researchers in automation domains, data scientists and jobs that only deal with mining data like lawyers assistants jobs, etc. On the other hand things dealing with physical world or entirely unpredictable thing will be tougher to replace jobs of drivers, teachers for small kids for example. Another point to note is that the job losses to AI doesn’t mean that there will be no employees. It only means that the number of employees for a given task, where AI can automate part of it as discussed earlier, will reduce in future.”
A part of the industry does feel that AI will not replace analytic jobs rather provide support and ease for analytic jobs.
Srinivas G.R.,VP & Head, Business Solutions & Analytics at Brillio says “It is probably premature to state or conclude that Artificial Intelligence (AI) enabled analytics platforms and tools will take over analytics jobs. On the contrary, advancements in AI should help businesses accelerate analytics adoption and also integrate data driven decision making into day-to-day operations. AI can only assist in handling complex and routine analytical tasks easier and faster and can never replace human intuition and operational knowledge. As of now, AI enabled software platforms and tools don’t have the ability to explain why a particular output or recommendation is given. Business leaders will not have the confidence to adopt the output or recommendations of AI enabled platforms without knowing the underlying reasons and that’s why human intuition and expertise and judgement will come into play.”
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