Top 5 Technologies that will enable Digital Transformation in 2023

5 Technologies that will enable Digital Transformation

In this article we discuss technologies that will enable Digital Transformation

1.      Cloud Native Apps and Services:

One of the top technologies that will enable Digital Transformation, cloud native is a software development approach that leverages cloud computing to build and run applications in modern dynamic environments.

Consider a cloud native travel application. Each segment of the travel app works as a micro service for example – flights, buses, car rentals, or hotels. It means that you can build and deploy new application features as independent units that can work seamlessly when integrated.

Micro services save the productivity of developers, reduces downtime and cuts operational expenses. Traditional infrastructure increases the dependency between the application and the OS. This makes any app migration process risky and complex.

Cloud native apps are fast, agile, resilient, predictable, and manageable. Cloud native architecture is exemplified by containers declarative API’s, immutable infrastructure, and service meshes.

If you are looking to digitally transform your business application, there is no better choice than cloud native.

2.      Internet of Things (IOT)

The Internet of Things or IoT is influencing our lifestyle – from the way we react to the way we behave. From air conditioners that you can control with your smartphone to smart cars providing the shortest route, or your smartwatch which is tracking your daily activities.

IoT is a giant network with connected devices. These devices gather and share data about how they’re used, and the environment in which they’re operated. It’s sold on using sensors.

Sensors are embedded in every physical device. It can be your mobile phone, electrical appliances, vehicles, barcode sensors, traffic lights, and almost everything that you come across in your day-to-day life. These sensors continuously emit data about the working state of the devices.

IoT provides a common platform for all these devices to dump their data and a common language for all the devices to communicate with each other. Data is emitted from various sensors and sent to IoT platforms securely.

IoT platform integrates the collected data from various sources. Further analytics is performed on the data and valuable information is extracted as per requirement.

Finally, the result is shared with other devices for better user experience, automation and improving efficiency.

Let us look at a scenario where IoT is doing wonders.

In an AC manufacturing industry, both the manufacturing machine and the belt have sensors attached. They continuously send data regarding the machine health on the production specifics to the manufacturer to identify issues beforehand.

A barcode is attached to each product before leaving the belt. It contains the product code, manufacturer details, and special instructions.

The manufacturer uses this data to identify where the product was distributed and track the retailer’s ventric. Hence, the manufacturer can make the product running out of stock available.

Next, these products are packed and parceled to different retailers. Each retailer has a barcode reader to track the products coming from different manufacturers, manage inventory, check special instructions and many more.

The compressor of air conditioner has an embedded sensor that emits data regarding its health and temperature. This data is analyzed continuously, allowing the customer care to contact you for the repair work in time.

This is just one of the million scenarios. We have smart appliances, smart cars, smart homes, and smart cities where IoT is redefining our lifestyle and transforming the way we interact with technologies.

The future of IoT industry is huge. Business Insider intelligence estimates that billions of IoT devices will be installed within a few years resulting in a lot of job opportunities in the IT industry.

3.      Mobile Apps

You will find entrepreneurs hustling to kickstart their digital transformation efforts which are lined within the backdrop for several business hours.

While a considerably easy move after you alter your digital offering in step with the customers’ needs, things become a bit difficult after you start planning digital transformation for your business.

There are two important elements that businesses must specialize in when aiming to digitally transform their gear workflow and workforce – adaptability and portability. And by bringing their processes and communications on mobile apps, they are ready to hit both targets in one go.

Digitalization opens you to an omnichannel presence that enables your customers to access your services or products from across the world.

So, the role of mobile applications will be introduced in all the areas which are often the key areas of digital transformation challenges that an enterprise face like:

1. Technology integration
2. Better customer experience
3. Improved operations and change organizational structure

Mobile apps are playing a job in advancing businesses internal digital transformation efforts by:

Utilizing the AI in mobile apps: The benefits of using artificial intelligence for improving customer experience is uncontested.

Through enabling technologies for digital transformation, businesses have started using AI for developing intuitive mobile apps using technologies like language processing, tongue generation, speech recognition technology, chatbots and biometrics.

Artificial intelligence doesn’t just help with automation of processes and with predictive preventative analysis, but also with serving customers in the very way they require to be served.

Onset of IoT mobile apps: The time when Internet of things was used for displaying products and sharing information is sliding by. Enterprises are now using Internet of Things mobile apps to work smart equipment in their offices and making the provision chains efficient and transparent.

Internet of Things mobile apps are finding ways to strengthen their position within the business world. But another thing is about making the involved decisions via real time analytics.

In the current business’ world, access to real time analytics can provide you with a powerful competitive advantage. Mobile applications are an excellent way for businesses to gather user data and interact with them.

Portability: Portability is an enterprise ecosystem that enables employees to figure as per their convenience. While it shows less impact within the short term, in the near future, it will play an enormous role in how productive a team is.

 4.      AI and ML: The Leading Technologies Driving Digital Transformation

Every day, a large portion of the population is at the mercy of a rising technology, yet few actually understand what artificial intelligence is. Thanks to books and movies, we have formed our own fantasy of a world ruled or at least served by robots.

We’ve been conditioned to expect flying cars that steer clear of traffic and robotic maids whipping up our weekday dinner.

But if the age of AI is here, why don’t our lives look more like The Jetsons? Well, for starters, that’s a cartoon.

And really, if you’ve ever browsed Netflix movie suggestions or told Alexa to order a pizza, you’re probably interacting with artificial intelligence more than you realize. And that’s kind of the point.

AI is designed so you don’t realize there’s a computer calling the shots. But that also makes understanding what AI is and what it’s not a little complicated.

In basic terms, AI is a broad area of computer science that makes machines seem like they have human intelligence. So, it’s not only programming a computer to drive a car by obeying traffic signals, but it’s when that program also learns to exhibit signs of humanlike road rage.

As intimidating as it may seem, this technology isn’t new.

In fact, for the past half a century, it’s been an idea ahead of its time. The term artificial intelligence was first coined back in 1956 by Dartmouth professor John McCarthy.

He called together a group of computer scientists and mathematicians to see if machines could learn like a young child does, using trial and error to develop formal reasoning.

The project proposal says they’ll figure out how to make machines use language, form abstractions and concepts, solve kinds of problems now reserved for humans, and improve themselves. That was more than 60 years ago.

Since then, AI has remained, for the most part, in university classrooms and super secret labs.

But that’s changing. Like all exponential curves, it’s hard to tell when a line that is slowly ticking upwards is going to skyrocket. But during the past few years, a couple of factors have led to AI becoming the next big thing.

First, huge amounts of data are being created every minute. In fact, 90% of the world’s data has been generated in the past two years. And now, thanks to advances in processing speeds, computers can actually make sense of all this information more quickly.

Because of this, tech giants and venture capitalists have bought into AI and are infusing the market with cash and new applications.

Very soon, AI will become a little less artificial and a lot more intelligent. Now the question is, should you brace yourself for yet another Terminator movie live on your city streets? Not exactly. In fact, stop thinking of robots when it comes to AI.

A robot is nothing more than the shell concealing what is actually used to power the technology. That means AI can manifest itself in many different ways. Let’s break down the options first.

You have your bots. They’re text based and incredibly powerful, but they have their limitations.

Ask a weather bot for the forecast, and it will tell you it’s partly cloudy with a high of 57. But ask that same bot what time it is in Tokyo, and it’ll get a little confused. That’s because the bot creator only programmed it to give you the weather by pulling from a specific data source.

Natural language processing makes these bots a bit more sophisticated. When you ask Siri or Cortana for the location of the nearest gas station, they are really just translating your voice into text, searching for the answer, and reading it back to you in human syntax.

So, in other words, you don’t have to speak in code.

At the far end of the spectrum is machine learning and it is one of the most exciting areas of AI. Like a human, a machine retains information and becomes smarter over time.

But unlike a human, it’s not susceptible to things like short term memory loss, information overload, sleep deprivation, and distractions.

But how do these machines actually learn?

Well, while it may be easy for a human to know the difference between a cat and a dog, for a computer, not so much. When you’re only considering physical appearance, the difference between cats and dogs can be a little gray.

You can say cats have pointed ears and dogs have floppy ears. But those rules aren’t universal.

Between tail length, fur, texture, and color, there are a lot of options, and that means a lot of tedious rules.

Someone would have to program manually to help a computer spot the difference. But remember, machine learning is about making machines learn like humans.

Like any toddler, that means they have to learn by experience. With machine learning, programs analyze thousands of examples to build an algorithm.

It then tweaks the algorithm based on if it achieves its goal.

Over time, the program actually gets smarter. That’s how machines like IBM’s Watson can diagnose cancer, compose classical symphonies, or crush Ken Jennings at Jeopardy.

Some programs even mimic the way the human brain is structured, complete with neural networks that help humans. And now, machines solve problems generations have long imagined.

The ramifications of AI visualizing a society where machines seek revenge and wreak havoc on human society. However, the more logical and pressing question is, how will AI affect your job? Will it make your work obsolete?

Just like the Industrial Revolution, it’s not human versus machine. It’s human and machine versus problem.

The point is that artificial intelligence helps you accomplish more in less time, taking on the repetitive tasks of your job while you master the strategy relationships. That way, humans can do what they do best – be human.

5.      Real-time analytics

We are now living in a world where real time data is becoming more and more important.

Companies have realized that data has a shelf life. And the sooner we can use this data and turn this into insight, the more it can be useful for our companies.

So real-time data is about using and analyzing this data as soon as it becomes available. The benefits of real time data analysis means that we can make faster and better business decisions.

You can also create more intelligent and smarter products and services like recommendation engines and customizing your services. You can improve and automate your business processes by using technologies that enable digital transformation.

Let’s look at some examples here. Real time data analytics is already used by banks to detect potential fraud. They will use artificial intelligence algorithms to monitor your card usage, purchase patterns, and geographic locations for potential fraud.

They can also add another layer of security checks into this. Websites and apps are now using real-time data. So, their apps might monitor your location, say the airport, and they can identify micro moments when they run an ad for travel insurance.

Micro moments are enabled by analyzing your internet usage, searches, and app usage to produce better services.

Real time data also enables automation. Things like self-driving cars or self-flying planes and ships that can autonomously cross the oceans wouldn’t be possible without real-time analytics.

These systems use camera data, sensor data, LiDAR data that is continuously evaluated and streamed and processed on the spot.

Without real time analytics, it would simply be impossible. In order to use real-time analytics, companies need to have automated data feeds. And so much data is not available from anywhere.

Satellite data, web, and social media data can be collected. However, you need to make sure you are streaming data into your systems in real time, and you have the infrastructure in place to process it.

Hence, you need data feeds and systems in order to use real-time and analytics.

The good news is that a lot of this is now available as a service.

Small and medium sized companies can now use real time analytics capabilities from companies like IBM, Microsoft, and Amazon to connect their systems to weather data and predict customer behaviors.

So, their apps might monitor your location, and they can identify micro moments when you might need travel insurance. You simply rent a bit of server space.

They might already have automated data feeds from weather services and satellite data and so on available. You simply subscribe to it and start using it as the world becomes more data driven. Streaming data and real-time analytics become increasingly important for businesses.

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