2020 embodies great opportunities and great challenges for corporate leaders. It is always important to remember that adopting change, adopting new technologies and trends will ensure your organization remains competitive in the market. Make no mistake in this regard, resisting change will leave your company behind. Those who focus on true digital transformation will grow their business. Are you brave enough to apply these trends that will reshape the future?
Television shows like the Jetsons of the 1960s predicted that the 21st century would be full of flying cars, and robots in the air would be part of our daily lives. October 21, 2015 marked the point where Marty McFly (Michael J. Fox) traveled in 1989, Back to the Future Part II, a sequel to the time travel classic. The future he found was a future that captured the imagination of millions – today we live in a world dominated by live broadcasts, smartphones and social networks.
In 10 years, or even less, service applications such as Uber, Lyft, DoorDash, AirBnB and others have unearthed millions of users and become available to almost everyone’s smartphone.
Personal assistants such as Siri and Alexa have been involved in most of our lives. It would be wrong for everyone to say that the world has not changed in the past 10 years. This technology growth and change is likely to continue over the next decade or so.
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It brings together many game-changing technology trends that we have adopted (or have already adopted) in 2020. While some things are already common findings in existing and modern business, other new technologies are “main choices” to drastically change the way we live, work and socialize. As modern technology we know and love develops with new use cases and even newer applications, we will begin to see new benefits and opportunities.
Hyper-automation raises task automation to the next level. It is the application of advanced technologies such as artificial intelligence (AI) and Machine learning (ML) to automate processes (not just tasks) much more effectively than traditional automation capabilities. Multi-machine learning to combine business is a combination of packaged software and automation tools. Hyper-automation requires a combination of tools to help support the reproduction of places where people are involved in a task. This trend started with robotic process automation (RPA), but it will grow with the combination of process intelligence, content intelligence, AI, OCR and other innovative technologies.
The multi-experience deals with a huge transition from a two-dimensional display and keyboard interface to a much more dynamic, multi-mode interface world where we dive into interactive technology and surround us. Multi-experience currently focuses on immersive experiences using augmented reality, virtual reality, mixed reality, multi-channel human-machine interfaces and sensing technologies.
Artificial intelligence-supported speech platforms have changed people’s interactions with the digital world. Beyond conversations, virtual reality (VR), augmented reality (AR), and mixed reality (MR) are changing the way people perceive the digital world. This combined change in both perception and interaction will result in future multisensory and multimodal experience. Over the next decade, this trend will become what is known as ambient experience.
Democratization of Technology
Democratization of technology refers to the process by which access to technology continues to become more accessible to more people.
Democratization of technology means providing people with easy access to technical or business expertise without extensive or expensive training. This is already widely accepted with the rise of the developer. Historically, automation has been managed and deployed by IT, but the advent of robotic process automation has changed this with the advent of digital workers. We are now seeing new generation citizen developers like business analysts who are closer to business challenges and can program and automate digital workers to help them do their jobs.
This trend will focus on four key areas: application development, data and analytics, design and information. According to Gartner, these could be tools designed to “produce synthetic training data that help create a significant barrier to ML model development”.
New technologies and improved user experiences will empower people outside the technical industry to access and use technological products and services.
Human augmentation explores how technology can be used to provide cognitive and physical improvements as an integral part of human experience. This augmentation leverages technology to physically and cognitively increase human abilities. Companies like Boston Dynamics have developed a wide variety of human augmentation devices that can be used in factories or on the battlefield.
We have already seen the proliferation of smart devices and smart wearable devices. New applications include the use of these wearable materials to increase worker safety in the mining industry. In other industries such as retailing and travel, wearable materials can be used to increase worker productivity and improve human ability.
Transparency and Traceability
Consumers, who are increasingly aware that their personal information is valuable, demand control. Many agree that the risk of securing and managing personal data increases. Beyond that, governments are enforcing strict laws to ensure this. Transparency and traceability are critical to support these digital ethics and privacy needs.
More legislation, similar to the European Union’s General Data Protection Regulation (GDPR), is likely to come into force worldwide in the coming years.
This is another cause for concern, as many organizations deploy artificial intelligence and use machine learning to make decisions instead of people. There is a need to explain explainable AI and AI governance. This trend requires focusing on the following key elements of trust: honesty, openness, accountability, competence and consistency.
Distributed cloud is how the cloud changes. Many thought the cloud was independent of location. But now with the distributed cloud, the physical location of the locations of these data centers is becoming increasingly important. It becomes much more important to address regulatory issues and delay issues and such things.
The cloud now expands its territory and becomes a distributed cloud; this is the overall cloud provider, taking responsibility for the operation, management, updating and development of the services, while the distribution of shared cloud services to different locations. This represents an important shift from the central model of most public cloud services and will lead to a new era in cloud computing.
Cryptocurrency and Practical Blockchain
The recognition of “practical Blockchain” is important here: While the Blockchain has been on the market for several years, it has been slow to distribute commercially due to some technical and management problems in technology. Blockchain has the potential to reshape industries by building trust, transparency between business ecosystems, and exchanging value, potentially reducing costs, reducing transaction extension times, improving cash flow and movement of materials.
The report says another area where Blockchain’s potential is identity management. Smart contracts can be programmed into the Blockchain where events can trigger actions; For example, payment is made when the goods are received. However, Brian Burke of Gartner says Blockchain will not mature for enterprise deployments because of a number of technical issues such as poor scalability and interoperability. “Despite these challenges, the potential for significant disruption and revenue generation means that organizations should start evaluating the Blockchain even if they don’t anticipate aggressive adoption of technologies in the near term,” he says.
When complementary technologies like AI and IoT begin to integrate, Blockchain will see tremendous growth in the organization.
Evolving technologies such as hyper-automation show how real digital transformation has changed in the business world. However, these technologies also create vulnerabilities through potential new attack points. Future AI security will have 3 basic perspectives:
1) Protection of AI-supported systems, secure AI training data and trained pipelines and machine learning models;
2) Using machine learning to understand the patterns and using artificial intelligence to improve security defense, uncover attacks and automate parts of cyber security processes;
3) Predict the negative use of AI by attackers – to identify and defend these attacks.