Artificial Intelligence + big data = the future of outsourcing?

Despite the rising interest to artificial intelligence and big data these days, the interaction between them – which seems to be very effective and useful – is poorly understood. Business heavyweights could gain new business options, analytical information and productivity more than ever before by combining AI and big data working together. The expanded range of traditionally outsourced options like finance, recruitment, HR, and security is an example of the progressively beneficial part AI and big data taking in it.

Some people expect that the alliance of these two and other virtual services will let to forecast human influence on the market precisely and market trends as it has already influenced the process of stock market functioning by generating increasingly more data. For example, in more regular and common life it can be seen through Google’s tendency to use more and more data to define objects in images. Artificial intelligence is the key to the functioning of recommendation’s system for Amazon; it is the principle of Deep Face friend tagging option on Facebook.

What is more interesting, the expanding industry of the Internet of Things, so-called IoT, shifting the process of business, consumers and governments communication with the real world. Gartner predicts that where will be 20.8 billion devices connected to consumers and business organizations in 2020, an IDC forecasting 7.1 trillion US dollars by 2020. As a result, the growing scope of data generated be means of these devices create new issue that factories would face – how to cope with all this information. Probably they will try to find experts to solve this problem, that can’t set aside. Virtual assistant could serve as an analyzing expert of the incoming information to sort it properly, because some options cannot be performed by AI. So enterprises will have the need to use AI and big data combinations for decision-making and providers of operational usefulness options.

It is quite mistaken to think that using big data and AI means more options with a lower cost for services . They are the instruments to enlarge the receiving of business outcomes, while, for instance, automatization is a tool of service for business. The received data must be stored and analyzed accurately. Enterprises have to perform these options online, in real time, to handle with it effectively.

Nowadays the main accent must be made on the organizational point of the process to consider all useful information and capture it to define what’s important immediately to apply the results in future planning, looking forward and to stay relevant in the changing flood of events. It becoming more vivid that traditional approaches to analyze information is not as effective, as it is needed in a modern world to stay viable and prosperous.

One more thing that is important to mention – proper sets of skills. Machine can’t afford the causation, just correlation, and these two things are not the same. Domain expertise is the stumbling point of expanding the use of big data and artificial intelligence, and virtual assistant could perform this to get more benefit of it. It will take a lot of time and work to shift the principle of AI and big data work from processing to teaching level on the operational side of the issue. This system is lacking human intellect, that virtual assistant could offer. When it comes to gathering data – AI and big data are indispensable, but analyze and causation is the work for virtual assistant.

We have to draw the line between the shattering impact of artificial intelligence and big data on enterprises in future and the profitable use of this combination. They can serve as a trigger for the revolution in the business tools range. The proper use of such technology establish the better connection between consumers and producers.

The issue of this approach is to adopt the technology as the part of the fundamental principles of business. But the opportunities of big data and AI are endless and definitely worth it in cases where the forecasts are necessary, not talking about operational processes and management improvements.