The Business of AI

Up until recently, artificial intelligence (AI) has always been working in the background. For the past few decades, it mostly handles mundane things like repetitive tasks, data processing or number crunching. 

In the enterprise, its number one use is to process and analyse massive amounts of data (big data analytics), to uncover hidden patterns, correlations and present actionable solutions that businesses can use to their advantage. 

Take for example, your company wants to predict the outcome of a decision it is about to make. You feed the AI data like past year performance, and other related data. The AI then crunches through the presented data and churns out multiple possible scenarios. All that's left for you to do, is to pick out your desired scenario, and the solution that provided the outcome. 

While this is a gross oversimplification of what AI actually does for enterprises, there's no doubt that can be an important tool in the decision-making process of any company, across almost every industry.

In 2016 however, a significant amount of resources have been used by major tech companies to enable an evolution of what AI can do. An example of this shift would be the soon-to-be ubiquitous chatbot.

In the retail industry, chatbots are built specifically to enhance customer experience. This year, Uniqlo is said to be building an intelligent Facebook chatbot (together with MindMeld) that is able to engage users by understanding and answering their queries.

Through the bot, users are able to ask product-related questions, and receive the answers they want immediately. That's because the bot is able to access and learn about Uniqlo's large inventory of products, allowing them to return the best possible answer.

Other famous chatbots include Amazon's Alexa, Apple's Siri, Google's Allo, Microsoft's Cortana and IBM's Watson. While not built for business use, these chatbots are currently are the forefront of chatbot technology, and are used as benchmarks for what chatbots can do.

So how does it work?

What makes the aforementioned chatbots so powerful (and promising) is their ability to learn - otherwise known as machine learning. And at the cutting edge of machine learning is a technology that is currently known as deep learning.

In a nutshell, deep learning uses complex algorithms to process data, or gain experience. It uses the experience learned to make decisions on how to process other data - ultimately forming a deep neural network. 

The resultant network can then be applied to massive and complex datasets (images, speech, videos, etc...) and reach conclusions as fast or even faster than a human mind can. 

An example of what this technology can achieve, can be seen in today's self-driving cars that are currently being developed aggressively by car and tech companies across the globe. 

Is it time to invest in artificial intelligence? 

Investments into the field of AI, has been reported to have tripled since 2013, and will only continue to pile up. If artificial intelligence is good enough to drive cars, investing in AI is only a matter of “when.” 

As technology reshapes the global economy, AI's abilities to enhance decision-making precision and streamlining business processes (cut costs with innovative solutions) could prove to be the deciding factor between success or great success. 

A current example that most companies in any industry can start to explore are chatbots. It's a simple solution that's backed by steady improvements that companies can use to enhance customer engagement and satisfaction levels.

Having a well-rounded chatbot that engages with a large number of customers at any given time allows a company to partially (or fully) replace their call centres and remove the costs associated with them.

If you can foresee any areas in your business that can be automated, it might be time for you to start exploring the viability of using artificial intelligence.