Blockchain, augmented analytics and artificial intelligence will drive disruption and improve business opportunities.
The way fictional movies are portraying artificial intelligence (AI) and robots provide a fascinating glimpse into humanity’s relationship with technology.
Companies are using AI-driven robotics to connect with customers on a deeper level, automate tedious tasks and logistics. These AI-driven robots are just one example of autonomous solutions. To explore more about these technologies, read the following trends that will impact and transform industries in the coming years.
1. Autonomous Technology
Autonomous technology (like robotics, drones, vehicles, and appliances) is a rapidly growing trend, with its broad impact and use in this digitally transformed era. It uses Artificial Intelligence (AI) to perform tasks traditionally done by humans. With the incorporation of Artificial Intelligence (AI) into an autonomous ecosystem, it is awe-inspiring to envision the transformational possibilities that lie ahead for various industries.
Use of autonomous technology in several areas are illustrated below:
- Travel into space to collect scientific information, etc.
- Reduces accidents caused by drivers’ negligence or other conditions such as weather, etc.
- Helps farmers decide when, where and how much irrigation, fertilizer, and pesticides their farm needs.
- Monitors crops and analyzes soil quality, etc.
- Tracks the state of all the devices in your home
- Enables you to control all your devices without storing any of your data in the cloud
- Turns on lights when the sun sets
- Dims the lights when you start watching a movie on your Chromecast, etc.
In the future, virtually every application, service and IoT object will possess some form of AI to automate processes.
2. Augmented Intelligence
Augmented analytics is a smart solution that every business wants to get their hands on. It enables companies to go beyond just figuring out what is happening in their business and start predicting what’s going to happen in the future.
It’s a tiresome and time-consuming process for data scientists to prepare, analyze, and group data before drawing conclusions from them. It means businesses can miss critical insights the data scientists don’t have time to explore. Here, augmented analytics will help data scientists to explore more insights from data. It uses machine learning and natural language processing to expand the automation process.
With augmented analytics, data scientists can:
- Bring strategic value to data reports and forecasts
- Prepare, shape and clean data more quickly and easily
- Make dashboards and visualization more flexible and powerful.
In the future, more than 40% of data science tasks will be automated, resulting in increased productivity of data scientists. By adopting augmented analytics, data insights will be more readily available across the business, including analysts, decision-makers, and operational workers.
3. AI-driven software development
AI-driven development focuses on tools and techniques for embedding AI into applications and using AI to generate other AI-powered tools. This trend is evolving in two aspects:
- Enterprises prefer the tools that target professional developers instead of data scientists. While data scientists have to build AI infrastructure, AI framework and its platform, professional developers just have to infuse AI-powered capabilities into an application without the help of data scientist.
- Ready-to-use AI tools are used to create AI-powered solutions which will enable companies to increase their productivity faster, reduce costs, and improve relationships with customers. This approach is empowering businesses by automating tasks related to the development of AI-powered solutions. Technologies that are assisting developers in speeding up the development process are:
- Augmented analytics
- Automation testing
- Automated code generation
- Automated solution development
Developers that are using predefined models delivered as a service will be in high demand in the market. It enables more developers to utilize the services, hence increasing their efficiency.
4. Digital twin
A digital twin is a virtual representation of a real-life object, process or system. It bridges the gap between the real world and tech. While the concept of a digital twin is not new, it’s only because of IoT that it has become cost-effective to implement.
Today’s digital twins have evolved by becoming more:-
- Robust, with a focus on how they support specific business outcomes
- Potential in linking to the real world
- Advanced in interacting with AI and evaluating “what-if” scenarios.
How a digital twin works:-
- First, smart components with sensors are incorporated into a physical object.
- Then components are linked to a cloud network to process all the data the sensors monitor.
- This input is examined by experts to help businesses.
Digital twin technology helps companies drive innovation. With its advanced monitoring, analytical, and predictive capabilities, it will better understand customers’ needs. On the other hand, it will enhance existing products and services by improving the customer’s experience.
“Digital twins are becoming a business imperative, covering the entire lifecycle of an asset or process and forming the foundation for connected products and services. Companies that fail to respond will be left behind”, says Thomas Kaiser, SAP Senior Vice President of IoT.
Tech-giants using digital twin solutions:-
- Microsoft Azure IoT adopts the concept of ‘device twin’ , as part of their device management solution.
- Amazon has ‘device shadow’ as its version of a digital twin.
- IBM has a ton of marketing collateral around digital twins.
5. Edge computing
Edge computing is causing significant disruption in industries and business models. In edge network, data collection, information processing, and delivery are placed closer to the local source instead of in a data center. It reduces latency and increases safety and security.
The fundamental part of this technology is the seamless integration between IoT and Cloud (between the physical world and the world of computation.) An edge computing application uses:
- Processing power of IoT devices to filter, pre-process and aggregate IoT data
- Power and flexibility of Cloud services to run complex analytics on those data.
There will be a steady increase in the embedding of sensors, storage, actuators and advanced AI capabilities in edge devices. In general, intelligence will shift towards the edge in a variety of endpoint devices, ranging from industrial devices to automobile power generators.
Read more- Optimize system by using edge- IBM and Edge and IoT- IBM
6. Immersive technology
Immersive technology transforms the way users interact with the world. Some types of immersive technology extend reality by carpeting digital images on a user’s environment. Others create a new reality by completely padlocking a user out from the rest of the world and immersing them in a digital environment.
Types of immersive technology include: 360, augmented reality (AR), mixed reality (MR), virtual reality (VR), and extended reality (XR). These technologies will lead to a new immersive experience by changing the way users perceive the world.
Immersive Technology used to be something you would read about in Sci-Fi books or watch in Sci-Fi movies. Now, apart from gaming, this technology has many different applications. Some of them are listed here:-
- In marketing and advertising– Elevate the ad experience for consumers.
- In healthcare– Allows medical students and doctors to do surgery simulations, helps to relieve a patient’s pain by immersing them in an experience that distracts them from what’s going on, etc.
- Education- Enable students to have field trips in VR from their classroom, create immersive content for them so that they can learn better, etc.
In the coming years, 70% of enterprises will be experimenting with immersive technologies for consumer and enterprise use. Conversational platforms, virtual personal assistants and chatbots, will embed enhanced sensory channels to detect emotions based on facial expressions. They are expected to become more conversational in interaction.
Blockchain is a distributed, decentralized ledger, cryptographically signed and immutable transactional record shared by all participants in a network.
Every second of every day, businesses exchange value (transactions) with suppliers, partners, and customers. Blockchain for business provides a way to complete these transactions in a fast and precise way. It allows companies to trace transactions. With this, companies can work with third-parties without any need for a mediator (centralized party). It will significantly reduce business friction.
Things that make blockchain good for businesses:-
- Distributed:- Itcreates a shared system of record among business network members, eradicating the need to reconcile different ledgers.
- Permissioned:- Each member of the network must have access privileges.
- Immutable:- It permanently records validated transactions. Even a system administrator can’t alter the transaction.
Blockchain technology began in finance. Now it has expanded to other sectors as well: government, healthcare, manufacturing, supply chain, and others. It helps to build more efficient enterprise business models, facilitate transactions, and improve cash flow.