AI implementation trends

AI is the hottest term in tech these days. Media stories predict, and human pundits argue, everything from AI solving all of humanities woes to AI’s subjugating humanity and charting its own course.

What we do know for sure is that AI will significantly transform the way companies function internally, as well as  how they interact with their customers.

Starting today we’ll look at some of the ways AI is disrupting and transforming different industries.

In this first post we will look at leading industry of AI development – IT. And then will see how this progress is applied in more traditional sectors such as banking and insurance.

AI progress in IT

It’s commonly recognized that AI changes anything it touches, but to understand how AI will affect every industry the best place to start is on its home turf — IT. The great majority of the rapid progress we see today with AI implementation in different spheres is the work of leading tech companies that invest huge amounts of money in research and developing software and hardware.

Let’s see what’s going on at the forefront of AI technology.  What the most recognized industry giants, Amazon, Apple, Google and Microsoft have achieved and what they offers for business.

Virtual assistant war

Tech giants believe that future of our interaction with computers and other devices will be by voice, so they focused their effort on developing voice recognition technology. The results are seen in the use of virtual assistants in a range of different devices. The major players produced the most well know assistants, Alexa, Siri and Google Assistant.

Skill set of virtual assistants are remarkable; they play music anywhere in your home, but also shop, control some smart home services, and interact with other devices. They are a long way from reaching their full potential, but the speed of development  is amazing.

What does that mean for your AI strategy?

Voice recognition technology is getting better and that opens great opportunities to build human-like voice interaction instead of touch interaction.

Recommendation Engine

Netflix, an entertainment leader, has proudly named itself a data company. And that’s true. More than 80% percent of the shows people watch on Netflix are discovered through the platform recommendation system. See here.

The algorithms behind these stats go far beyond 5 star ratings or recommendations based on user preferences. Instead, they perform deep analysis of actual user behavior, not only what people watch, but when they pause, when they leave, what was on the screen when that happened, etc. AI technology interprets this data and provides the recommendation of what to watch next.

What does that mean for your AI strategy?

This is more proof that a user-centric strategy, although costly, eventually pays off. The better you know your user the more profitable they will be for your business.

Shopping at Amazon Go

Aside from the human reaction to a radically different shopping experience, the opening of the first Go store  is a good example of  how businesses can radically change with AI implementation. When different types of technology successfully work together the results can be astonishing.

What does that mean for your AI strategy?

There is great potential connecting different types of technology, so be creative as you develop your strategy.

AI services by the click

Even as the tech giants fight for dominance, they are sharing their advanced knowledge and progress.

In 2017 they brought MLaaS (machine learning as a service) products to the market.

Amazon AWS MLaaS, Microsoft MLaaS, Google MLaaS all offer pre-trained neural networks for image, video, voice, and natural language processing.

This makes it much simpler for companies, from startups to much larger and older, to develop their own AI models. It substantially reduces the infrastructure costs needed to develop your own AI program, as well as limiting the number of data experts required.

What does that mean for your AI strategy?

Implementation of AI technology seems more accessible and less costly now. Easy access to developments tools opens the opportunities for all kinds of niche startups. However, as AI gets more affordable it also means higher levels of competition. So you should start earlier crafting an AI strategy for your business.

How AI is changing Banking

The banking industry is betting big on AI technology. AI is being applied across many areas from recommending products to fraud detection.

Customer service

Being one of the oldest industries banks have maintained “traditional” customer service for a long time.

However, due to digital disruption business landscape has been changed significantly. New competitors, such as Apple Pay and Alibaba Pay, who are better positioned to attract millennial customers; new forms of distribution models and changing customer preferences are forcing banks to totally rethink their customer strategy.

There are two main direction working on this problem: improving self-service and back-office operations. Chatbots are successfully used for both direction.

Integrated in mobile apps it’s capable to make payments, analyze spending, help manage money and prevent overspending.
Using chatbots as operations assistants allows to increase efficiency and productivity.

As AI technology advances we will see this trend growing. A forecast by Juniper research predicts a 90% rate of bot interaction by 2022 in the banking sector.

Algorithmic Trading

Although algorithmic trading has been around for a long time, AI brings new opportunities. Previously, trading strategy had to be evaluated first by a person and then software could replicate those algorithms for trading. Now people are not involved in creating the strategy; the  system analyzes the data, uncovers patterns and indicators and builds more reliable trading strategies.

Some systems are using natural language processing to analyze data from news, social media, and other sources to understand context and correct the trading strategy accordingly.

Asset management

While the question of replacing portfolio-managers with AI tools is still arguable, it’s obvious that the capability of AI and deep learning can improve the decision making process. AI is able to analyze large volumes of data creating cross-field patterns and indicators, which help to build more sophisticated and precise models, in which not-obvious to humans risks and investment opportunities can be recognized.

Data-based lending decision

AI provides new possibilities for improving the credit profiling system. Banks want to minimize risk by gathering and analyzing more information than ever before. Now scoring systems can analyze online activities, interests, and other data points for better decisions.

Security and fraud detection

Security and fraud detection has always been a top priority for banks. These days AI has significantly improved fraud detection. Previously fraud detection rules and check-lists were designed by humans. Now, deep data analysis and the advanced analytics capability of AI can crunch through large big volumes of data in real time detecting anomalies previously unseen.

AI trends in Insurance

The insurance industry is an extremely competitive market. In order to win, leading companies are exploring and embracing every opportunity to improve business performance. AI technology has enormous potential to do just that opening huge opportunities for future growth in both – better customer satisfaction and optimized business performance.

Current trends in the application of AI and machine learning include:


While practice shows that people are not ready to buy insurance products directly from chatbots, as a sale assistant chatbots work well. Being able to use natural language processing in real time helps sales agents to quickly identify the most suitable insurance option for the specific need, which provides a better customer experience.

Faster auto claim settlement

Insurance companies are already speeding up accident claims by allowing user to send pictures of the damage, instead of having to meet with a human adjuster. New apps will go a step further and provide almost instant cost estimates by integrating AI into their apps. See details here. AI tech will also takeover many back-office operations, such as estimating, claim processing and payments will be performed. This should reduce the average settlement time from several days to a few seconds. Insurance companies see this as a win-win — greater customer satisfaction and the elimination of people cost (according to GlassDoor, the average salary for a claims adjuster was around 50K in 2017).

Safer driving

Using machine learning and improved IoT sensors allows companies to develop new insurance products based on personalized behavioral models resulting in lower rates for better drivers.

In spite of all the benefits AI technology offers, AI is also driving the biggest challenge for insurance companies. AI empowered autonomous cars and that will change the market significantly. New business models, new partnerships and new ways to work with data are what’s in store for the industry in the near future.

Wrapping up

Swiftly developing AI technology and products are forcing companies of all sizes, both old line and new upstarts, to rethink customer experience and, hopefully, change it for better.

It also offers enormous opportunities for startups to create niche products to serve the needs of larger companies.

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