The global cognitive technologies market is expected to reach USD 49.36 billion by 2025. Here’s what its broad division looks like:

The technology is nowhere near its maturity and new avenues are sprouting up every day. The number of NLP users has already grown up to 62% from 53% last year. The machine learning adoption rate was 63% last year. Computer vision is growing at the CAGR of 31.65% and CAGR of robotics is 20.2%.

Cognitive technologies are capable of performing tasks that were previously restricted to human capabilities only. They have the potential to augment or replace human performance. Businesses have taken the heed and are increasingly utilizing cognitive technologies in their models. This trend is expected to grow at an exponential rate over the coming 5 years. But, here’s a word of caution; ill-informed and spotlight driven decisions will only lead to loss of time and resources (to bankruptcy in extreme cases). If planned appropriately, however, they have the potential to augment the existing returns exponentially.

If you are planning to benefit from these technologies, then we suggest getting a broader perspective on the available opportunities and then make an informed decision.

The Big Picture:

While many technology forerunners are using these technologies for improving their existing products and services, few others like Roomba robotic vacuum cleaners are using it to model a completely unique product offering. These radical inventions are creating new product markets and have the potential to overhaul existing product offerings. Google now aims to identify its users need for information and offer it beforehand. IBM’s Watson is giving data insights to its users. Unmanned vehicles, robotic caregivers and house assistants show great potential for mass adoption.

Applications of cognitive technologies to existing products and services fall into these three broad categories: product, process, or insight.

Product or Service Related Cognitive Technologies:

In the past, cost, time and quality parameters had linear links. Cognitive technologies have changed these trade-offs. Now all three of them are possible simultaneously.

Here are some of its fabulous examples:

Netflix’s usage would have dropped by a significant 75% devoid of its machine learning that suggests shows to its customers based on their previous likes. eBay is using machine learning to facilitate Russian language translation in English. When its customers type in Russian the algorithm matches the query to its English listings and shows related suggestions.

General motors is using computer vision to understand if the driver is paying enough attention to the road ahead. An unnamed company is using computer vision algorithms to detect similarities between positive breast cancer cases and mammograms. The algorithm can tell abnormalities from mammogram images. Some mobile phones check their user’s image before giving access to them. Amazon-Go is using computer vision to go cash-less.

Dominos is improving its customer experience by using Dom, an algorithm that lets customers place their orders using voice command. Audi is integrating speech recognition technology to engage drivers in a more natural conversation.

Process-Related Cognitive Technologies:

Cognitive technologies are helping automation in two ways:

• By augmenting existing worker productivity.
• By eliminating worker involvement in repetitive tasks.

Different algorithms are helping users diagnose their medical conditions, get basic medication and seek further consultation advice. Others are helping them sort and customize news and information. Automated chat boxes and voice response algorithms eliminate the need for ‘first-contact’ customer service. The Hong Kong subway system is using cognitive technologies to schedule its trains. In the process, it is able to save two days of planning. Twitter uses Natural Language processing to give its customers insights about their TV advertisements.

Insights-Related Cognitive Technologies:

Stevia is using cognitive technologies to get insights into its products. It is also using an algorithm “smart search” to improve its production by optimizing production cost and time. Intel is using machine learning to identify potential customers. BBVA Compass bank is using cognitive technologies to understand its customer’s sentiments on social media.

The Imperative Details:

Given the benefits of these technologies, their expansion to varied business areas is inevitable.

Before moving ahead with the inclusion of any cognitive technology, answer these questions:

• Do you need cognitive technology for a task or process?
• To what extent do you need it? Should it be completely automatic or semi-automatic?
• How cost-effective it will be? Will it boost your revenue immediately?
• Is it indispensable? Does your product, business model, or team depend completely on it?
• Do you have talent for it?

At the present time, most of the cognitive technology solutions (approximately 64%) are focused on marketing and sales. Its inclusion in other verticals is yet to arrive.