Will Cognitive AI replace existing Artificial Intelligence practices in the coming years?

While artificial intelligence (AI) is here to augment human thinking to solve complex problems, cognitive computing focuses on mimicking human behavior and reasoning to solve those problems. When paired together, these technologies, we get an advanced version of AI with cognitive capabilities. It is not here to supplant existing applications of AI. Instead, it will monitor how traditional AI processes data and fill gaps between data collection, insights and action. Generally, cognitive AI is interactive, contextual, and adaptive by nature. It also learns and constantly evolves as a new set of information comes to light.

The adage that data is the new oil holds true, and soon, every industry vertical will resort to either buying or selling data. The data not only enables digital disruption but also acts as a key differentiator, identified by volume, variety, velocity and veracity. The insights gained from data help organizations settle on choices and make informed decisions rather than go by impulses. Cognitive AI synthesizes data from various touchpoints and sources, analyzes the context, and weighs the evidence to offer outcomes, insights and solutions.

Over the past few years, artificial intelligence has been fundamentally redefining the very meaning of ideas, innovation, and inventions, as it transforms industries. It has been possible due to leveraging of big data analytics. However, with staggering speed and big data growth in the market, it is becoming difficult to make strategic decisions on time. At the same time, there is a huge shortage of professionals with data analytical skills. Even if AI can help mitigate this situation, but it is also prone to errors. Cognitive AI can address this conundrum and help a business become more analytical in its management and decision-making approach. It also enables brands to use sophisticated algorithms (diagnostic, predictive, and prescriptive analytics tools) to gain insights into consumer behavior and identify trends too. Cognitive AI is on the verge of being the future of next-generation enterprises, backed by automation. In fact, it is already being employed in many industries currently.

Finance: Cognitive AI can sift through financial data, bringing a  dramatic increase in the speed and accuracy of anti-money laundering (AML) investigations or identifying fraudulent credit card transactions in real-time. It can also analyze historical data to understand the parameters to be used for judging a transaction to detect fraud transactions. Moreover, for financial institutes, cognitive AI can combine behavioral data and demystify market dynamics with higher precision, thus aiding in better market trends forecast.

Customer Brands: Cognitive AI can offer personalized services by assimilating data about location, time of day, user habits, semantic intensity, intent, sentiment, social media, contextual awareness, and other personal attributes. Through automation, cognitive AI can plan brands based promotions quasi-real-time with end-to-end visibility in their supply chain, understand the demand and matching the two. Further, it also facilitates personalized media delivery and content monetization across various social media channels. It also minimizes the chances of failure with predictive planning of brand campaigns.

Supply Chain and Logistics: In this sector, cognitive AI offers a wide range of solutions like smart fleet implementation with real-time fleet analytical intelligence; predictive fleet repair and maintenance to boost fleet efficiencies and productivity; smart routing to manage fleets efficiently and to reduce the cost of delivery. It can also improvise distribution logistics with intelligent supply chain decision making.

Healthcare: Researchers employ cognitive AI to analyze blood samples, metabolism, speech and language patterns, and handwriting to understand risk factors associated with Alzheimer's disease, resulting in programs that can diagnose the disease six years earlier than previously possible. It is also being used in research on genomics, drug discovery, and population health. When connected with IoT devices, cognitive AI can process data from IoT devices to provide interactive solutions too.