Artificial Intelligence (AI) is inspired by the way the human brain processes information, draws conclusions, and codifies instincts and experience into learning. While human brains are great at certain activities such as parallel processing and sorting information, they can only use 1-16% of their brain power at a time. This is due to the overwhelming use of energy it requires. Thanks to advancement in technology and AI and Augmented Analytics, we are no longer held by the constraints of human capabilities. According to a report by Gartner, AI will create more than 2.6 trillion dollars of business value by 2021 and about 6.2 billion hours of worker productivity. As such, it will be impossible for investors to even think of investing in a company that doesn’t incorporate this kind of intelligence in its operations.
So, what can AI do that humans cannot?
Machine learning has come a long way from when it was in its inception. It allows for a system to get better with time and with more tasks being handled by learning and improving on itself. A McKinsey report showed that 20% of C-level executives across 14 industries and 10 countries relied on machine learning as a core part of business and decision making. For it to learn, it needs data so that it can identify patterns and correlations in the data which can be used for future reference. These methods AI uses to learn include unsupervised machine learning algorithms (MLA), supervised MLA, reinforcement MLA and Semi-supervised MLA.
All these methods vary in approach and execution but each has its own advantages which the business can benefit. By combining all of them, they ensure that data is analyzed quickly and efficiently to produce accurate models and predictions even in the largest of organizations. As compared to humans who can create two or three good models a week, machine learning comes up with thousands within the same time-frame.
Speeds up gaining accurate insights
Gaining insights without the right technology is not only time consuming, it’s also resource intensive. With AI, you can be sure of real-time analyses of relevant data that can easily be understood and used in business decisions. Once the data has been filtered and analyzed, democratization takes effect. Here, Citizen Data Scientists (CDS) and business users can find and accurately visualize correlations, predictions, expectations, and anomalies. This means that information will be attained at good speeds which will, in turn, translate to better more actionable insights.
Humans are biased in nature even if the bias is unconscious. As such, a human might make biased analyses that end up costing the company several insights. With AI, the playing ground is different. This means that due to their neutrality, they are able to identify where such patterns of bias are evident. Expert analysts will definitely explore their own hypotheses first because the process of finding patterns in data can at times be quite exhausting. This also means that humans are more likely to overlook something in an attempt to increase expediency. AI automatically deploys algorithms to find data correlations, relationships, outliers and clusters thus making the whole process faster and less prone to errors.
Ways AI directly benefits the company
Democratized augmented analytics improves efficiency, decision making and independence due to CDS. By integrating AI tools to the business, teamwork and collaboration will take over from traditional hierarchical structures.
Improvement of Smart Data Discovery and similar technologies impact Total Cost of Ownership (TCO) and Return on Investment (ROI). With AI, you can easily monitor these KPIs and use the data to make improvements where necessary.
Because CDS can easily understand the data without assistance from the IT department and specialized Data scientists, they can get more efficient and output more results. This also gives the DS and IT community a chance to focus on more specialized projects.
By utilizing AI, all aspects of the business will grow for the better. Better analysis and predictions will lead to a quantifiable analysis of pricing, financials, service offerings and business operations. As such the business will grow better and excel.