“The upheavals [of Artificial Intelligence (AI)] can escalate quickly and become scarier and even cataclysmic. Imagine how a medical robot, originally programmed to rid cancer, could conclude that the best way to obliterate cancer is to exterminate humans who are genetically prone to the disease.” – Nick Bilton, Renowned Tech Columnist
Artificial intelligence (AI) has always been a hot topic of discussion (as well as of debate!). While many consider it to be the future of humans, some look towards it as a threat considering it ‘replacement’ instead of the future of humans. This latter group includes renowned thinkers and stalwarts like Stephen Hawkings and Elon Musk to name a few. This fear of AI can be diminished and the complex debate can be fruitfully used for the betterment of Analytics by first knowing the difference between Strong and Weak AI.
Strong AI and Weak AI
Strong AI is the one as shown in science-fiction movies or the one which people usually talk about as mentioned in the previous paragraph. It performs all tasks mimicking humans and can optimize them based on values and feelings as well.
Weak AI (a.k.a Narrow AI) in contrast is used in vertical niches to perform specific programmed tasks. It can’t process data outside its specified domain. Such AIs are used nowadays, be it Personal assistants like Siri or driverless Cars, or AI Analytics. As interesting and complex as it can be, AI in Analytics is currently in the nascent stage (but growing exponentially) and has wide applications.
AI Analytics
AI Analytics include:
- Sentiment Analytics
- Data Mining
- Neural Network Applications
- Machine Learning
- Decision-making
- IoT Analytics
- Predictive Analytics
- Big data and Digital domain analytics
Real-Time Analytics and Quick Results…
With the use of real-time analytics algorithms, AI can suggest tweaks in the process almost in a fraction of seconds, that too by analyzing huge chunks of data constantly flowing in. This helps companies to optimize their processes and gain better profits. This thus becomes highly important for analytics teams to integrate AI into their operations to outperform the competition. In fact, within 5 years, AI Analytics may become a necessity for companies rather than an extra advantage, as it is the case now.
Also Check: How to Use ChatGPT & AI for (UPSC) Exam Preparation
Digitization + Internet = Best Platform for AI
With growing digitization and exponentially increasing usage of the Internet (specifically in countries like India), there is no reason for companies to stay away from AI. A humongous amount of data is being available publicly in the form of the internet, media, and social platforms. In addition to that digitization and synchronization of CRMs and POSs as well has led to huge opportunities for AI applications and recommended optimizations by studying permutations of relations between various business parameters.
Countless Opportunities and ‘Hidden’ Solutions
The use of AI in analytics opens new doors and countless opportunities for leading the company towards sustainable success. The best part of it is that it not only drastically eases the process of data collection but also unleashes the ‘hidden’ dimensions of it unseen by humans.
It brings in recommendations via parallel history testings and machine learning which happen to be accurate to the highest points. With help of AI, companies are increasingly targeting individual customers thanks to the holistic approach made available due to various data points. So it won’t be an exaggeration to say that companies now know about customers more than the customers know about themselves!
A Customer can’t predict his/her next purchase but the AI can!