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AI, PropTech and more...


AI Mythbusters: From Hype to Reality

May 22, 2019 - By LEVERTON Team

From recommendation engines, chatbots, image recognition to predictive maintenance- AI has been making headlines as the omnipresent technology with enormous potential to solve real-world problems and improve business processes. All thanks to the power of modern, faster processors, ongoing advancements in deep learning, and volumes of data that are being generated every day.

But for organizations to apply Artificial Intelligence (AI) into their business processes and see the true value, it is essential to understand how AI works, what it can, and cannot do. We are going beyond the hype to demystify four common misconceptions about AI.

1.         AI is replacing humans

AI is currently in a stage of so-called narrow AI or limited knowledge. It is amazingly good and accurate at solving singular tasks and in fact is doing it better than a human could ever do, but AI does not make humans obsolete. At least not anytime soon.

Although deep neural networks of machines mimic biological neurons of humans, they do work differently. AI today cannot perform complex, or multi-tasks that combine different problems into one learning, and AI does not understand the context the way humans do.

Take, for instance, auto-suggest feature. While AI can predict the next word, you want to type it can’t fully interact or takeover a human-like conversation because of a lack of understanding of human emotions.

While every day, algorithms are learning to solve new tasks and getting better at it, humans will still be vital for solving complex cognitive multi-tasks.   

2.         AI implementation is expensive

Due to the complex nature of AI, there is an assumption that AI can be costly with the need to invest in a brand new, expert-level team of data scientists. But today, enterprise-ready AI solutions are widely available and don’t require considerable investment into hiring a team of data scientists to implement and benefit from AI. Most companies offering an enterprise AI have a necessary team available to support implementation alongside providing training for the team.       

3.         AI= Automation

The terms "Automation" and “AI” are fully interchangeable, but it is essential to identify the key differences. Automation is a process of carrying out a specific task in an autonomous way but driven by a manual configuration. Meaning it needs to be set up the way you want an automated system to work. Essentially, you can think about automation as a "robot" that mimics human action. While AI does automate repetitive and mundane tasks well, it adds intelligence to it. By mimicking human intelligence AI is concerned with "thinking" and "learning". 

4.         You need tech wizards to implement AI

It is crucial to understand how to deploy AI technology to transform business processes. CIOs can explain their counterparts that AI does not require technical knowledge for enterprise AI adoption and to bring AI solutions into play.

Today any organization at any level can successfully implement AI! After all, we are all using AI every single day in one form or another to simplify our lives. Meaning, it would not be any different to start using it in your organization.