How AI And ML Are Transforming Businesses

AI and ML

“Once upon a time, there were businesses across the globe that used to rely on human resources for interaction with customers and other operational matters. Those days, technology had not hugged business like it has done today…”

This can very well be the words of a fairytale that your kids will be reading in schools very soon. The way artificial intelligence has laid a siege on businesses is something we can see everyday around us. In April 2016, Facebook empowered its Messenger application with bots powered by artificial intelligence. A journal from CIO also reported that 33,000 chat bots are powered by Messenger. Looking at the way, AI and ML is transforming businesses, the realm deserves a deeper look.


Where is the world heading?

A report from BofA Merril Lynch claims that the market of AI and robots will grow to USD 153 billion by 2020. By June 2016, AI had already received USD 974 million of funding. The number of patents being filed for AI and ML are increasing regularly. Can you imagine, a whopping 62% of the organizations across the globe will be using AI by 2018, as claimed by Narrative Science!


Which businesses can leverage AI and Machine Learning?

To analyze if a business can leverage the power of machine learning and can use AI for its operations, it is required to do a reality check as follows.

  • Are the majority of the tasks repetitive?
  • Are the repetitive tasks high in volume?
  • Does the business need limited judgement in those tasks?
  • Is the cost of the mistakes low in the tasks?
  • Do the tasks follow a fixed pattern?

If the answer to each of these questions is a “Yes”, then the business can certainly benefit from AI and ML.


How Can Businesses Start?

There are primarily two things that a business will need for making a move with AI and ML. Let’s look at them one by one.

Historical Data

A company must have huge volumes of historical data on the tasks which it wants to automate. Machine learning is all about machines learning from disposable data and continuous experience. Correct and relevant data is of prime importance for leveraging AI.

Business Case

The benefit of AI and ML must help in cutting costs for the business. Only then can AI and ML be considered viable options for business. Moreover, the value rendered by the two powers must be greater than the value your current logistics are providing.


What Are Its Benefits?

The benefits of AI and ML cannot be put into simple words. It can help cut costs, learn about consumer behavior and come up with better strategies to tap into your existing customer base. Let’s look into four major areas where AI and ML can help.


Machine learning systems can collect data on consumer behavior and come up with statistics to understand what kind of business operations help in customer delight. Chat bots powered by AI can engage in better, deeper and more meaningful conversations with customers online. The hyper-personalized interactions heighten the customer experience, which helps in retaining loyalty of existing customers and getting new buyers as well.

Jamie Condliffe from MIT Technology Review has opined that companies in 2017 are trying to have conversational interfaces into a multitude of hardware. Salesforce Einstein is a tool that takes all of your CRM data, analyzes it meticulously and makes predictions and recommendations for corporate strategy. It can also help you understand the time when your prospect is statistically most likely to open your email and respond to you.


AI and ML can help machines learn tasks quickly and perform with high levels of accuracy. This can help in reducing the workforce in a company, which further helps to reduce liabilities for a business. Robots sold by Fanuc can learn new skills in mere 8 hours and can perform them with 90% accuracy.  Artificial intelligence, when powered by machine learning algorithms, can also help automate data science. This can make AI even cheaper.


Systems powered by machine learning algorithms can help in making predictions of outcomes and possible failures too. Statistics and data can help systems to predict issues of the future. At AIG, machine learning is helping the business to anticipate insurance claims. Moreover, network outages are also predicted well in advance by AI-powered machines. The issues that used to consume valuable 3.5 hours of engineers, can now be solved in just 10 minutes. This quick resolution of over 145,000 technical issues has given back 23,000 hours back to AIG’s employees.


Machine learning can also help in recommending and implementing best practices at business. Toyota, for instance, has leveraged AI to understand the age group that is most often the victim of road accidents. Toyota Research Institute is leveraging machine learning and AI to design safer and more accessible automobiles for all kinds of people. Machine learning can also help drive self-driving cars. AI-powered systems can understand what works well and what does not, and based on the findings, they can come up with the best practices to be followed.


Branding And Marketing

AI-powered systems can understand the demographic dividend of a market and help devise strategies for brand management. Such machines can gather information on the taste of consumers in a particular region, the response of different age groups and the buying behavior of various segments. It can then decide what kind of offers and services to be offered to each segment and how to maximize profits along with minimizing investments. This way, a business can save loads of money by avoiding unnecessary investments and can reap better benefits out of the continuous efforts to stay on top of the curve.


AI and ML are no longer luxuries for businesses. Rather, they are elixirs for staying ahead in the competition. Without AI and machine learning, businesses will lose out on the competitive edge and possibly face loss of customers and market share. If businesses need to survive and sustain in this competitive world, then having AI-powered machines running machine learning algorithms and churning out predictions is a must.

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