Artificial Intelligence Security, Distributed Cloud, Hyper Automation, Multiexperience, Autonomous Things, Traceability and Transparency are some of the technological trends that will drive digital disruption in 2020 and will create opportunities for organizations that will be able to grasp and decline them. We present below the list of the 10 top trends presented by Gartner on the occasion of the Symposium 2019 in Barcelona, structured around the idea of "smart spaces focused on people", in other words we will consider how these technologies will influence people (eg customers, employees) and the places where they live (eg home , office, car).
Strategic technological trends have the potential to both create opportunities and trigger significant changes. The leaders of Enterprise Architecture and corporate IT should evaluate these trends to determine which trends can play a crucial role in their innovation strategies, to improve existing processes, products and business models, or create new ones.
Automation uses technology to automate the activities that once required human intervention. Hyper-automation deals with the application of advanced technologies, including artificial intelligence (AI) and machine learning (ML), to automate more and more processes and "increase" human beings. Hyper-automation extends through a range of tools that can be automated, but also refers to the refinement of automation (aimed for example at activities such as discovering, analyzing, designing, measuring, monitoring, re-evaluating). Since no single tool can replace humans, hyper-automation today involves a combination of tools, including robotic process automation (RPA), intelligent business management software (iBPMS) and artificial intelligence, with aim to make more and more decisions based on artificial intelligence.
Although not the main objective, hyper-automation often results in the creation of an organization digital twin (DTO), which allows organizations to visualize how functions, processes and KPIs interact to bring value. The DTO therefore becomes an integral part of the hyperautomation process, providing continuous and real-time information on the organization and guiding important commercial opportunities.
Multiexperience replaces the concept of "expert people in technology" with that of "expert technologies in human behavior". The perspective changes, the traditional idea of computers evolves from a single point of interaction to include multisensory and multitouchpoint interfaces such as wearable devices and advanced sensors for computers.
Domino's Pizza is one of the best known examples of the companies that have invested most in a multiexperience platform, going far beyond a simple mobile app to order pizzas: the multiexperience offered to its customers includes applications that access smart speakers, a " pizza tracker ”app to track in real time where your pizza is located, the use of autonomous vehicles and drones for delivery, and much more.
In the future, this trend will become what is called an environmental experience, but currently multiexperience focuses on immersive experiences that use augmented reality (AR), virtual (VR), mixed reality (MR), multichannel man-machine interfaces and detection. The combination of these technologies can be used for a simple overlapping of augmented reality or a fully immersive virtual reality experience.
Democratizing technology means giving people easy access to technical or specific skills without extensive (and expensive) training. Non-IT professionals increasingly have access to powerful tools and expert systems that enable them to exploit and apply specialized features beyond their skills and training. Democratization focuses on 4 key areas - application development, data analysis, design and knowledge - and is often referred to as "citizen access", a phenomenon that has led to the growth of figures such as citizen data scientists and citizen programmers.
For example, democratization would allow developers to generate data models without having the skills of a data scientist. Like? By relying on AI-based development to generate code and automate tests.
Human Augmentation refers to the use of technology to improve a person's cognitive and physical experiences. The term Human Augmentation evokes visions of futuristic cyborgs, but in reality it is nothing so new: human beings have "increased" parts of their body for hundreds of years. Glasses, hearing aids and prostheses have evolved into cochlear implants and wearable devices. For example, laser surgery to correct vision problems has become very common.
What if scientists were now able to "increase" the brain to increase memory or implant a chip to decode neural models? What if exoskeletons became a standard uniform for workers, allowing them to lift superhuman weights? What if doctors could implant sensors to track how drugs work within the body?
Technology is going far beyond the ability to replace a human ability, inevitably bringing with it a number of cultural and ethical implications.
Digital Ethics and Privacy are increasingly hot topics for individuals, organizations and governments. Consumers are increasingly aware that their personal information is valuable and requires control over it. Organizations recognize the growing risk of protecting and managing personal data and governments are implementing very strict laws to ensure that this happens.
Artificial Intelligence and Machine Learning are increasingly used to make decisions in place of human beings and this only increases the crisis of confidence that we are witnessing.
Digital Ethics, Data Privacy, the need for explainable and ethical Artificial Intelligence, are all critical issues that have emerged to try to find an answer to this ongoing crisis.
Digital Ethics and Privacy are increasingly hot topics for individuals, organizations and governments. Consumers are increasingly aware that their personal information is valuable and requires control over it. Organizations recognize the growing risk of protecting and managing personal data and governments are implementing very strict laws to ensure that this happens. Artificial Intelligence and Machine Learning are increasingly used to make decisions in place of human beings and this only increases the crisis of confidence that we are witnessing. Digital Ethics, Data Privacy, the need for explainable and ethical Artificial Intelligence, are all critical issues that have emerged to try to find an answer to this ongoing crisis. We need to start being transparent about how we use data, how we build our artificial intelligence models and how we use them. Transparency and traceability are fundamental elements to support the needs of Digital Ethics and Privacy.
Transparency and traceability are fundamental elements to support the needs of Digital Ethics and Privacy.
Transparency and traceability are not a single product or a single action. It is a series of actions, technologies and support practices designed to meet regulatory requirements, sanction an ethical approach to the use of AI and other advanced technologies and regain confidence in the eyes of our interlocutors.
Edge computing is a topology in which information processing and content collection and delivery are closest to sources of information, under the assumption that keeping local and distributed traffic will reduce latency. With Empowered Edge technology, IoT devices are increasing, laying the foundations for smart spaces, bringing key applications and services closer to the people and devices that use them.
For example, in the context of Conversational Platforms many of these systems today rely on Cloud-based remote services: it is hoped that conversational processes will take place in the Edge, not in the Central Cloud, in the near future.
Distributed Cloud refers to the distribution of Public Cloud services to locations outside of the cloud provider's physical data centers, but which are still controlled by the provider. In the Distributed Cloud, the Cloud provider is responsible for all aspects of the architecture, delivery, operations, governance and updates of the Cloud service.
The evolution from the Centralized Public Cloud to the Distributed Public Cloud inaugurates a new era Cloud computing.
The Distributed Cloud allows you to locate data centers anywhere. This solves both technical problems such as latency and regulatory challenges such as data sovereignty. It also offers the advantages of a Public Cloud service together with the advantages of a local Private Cloud.
Autonomous Things, or autonomous objects, which include drones, robots, ships and household appliances, exploit Artificial Intelligence to perform tasks normally performed by humans. This technology operates on a spectrum of intelligence ranging from semi-autonomous to fully autonomous and in a variety of environments including air, sea and land.
While autonomous objects currently exist mainly in controlled environments, such as in a mine or warehouse, they are evolving to be used in public spaces in the future. Autonomous objects will also switch from autonomous swarms to collaborative swarms, such as the drone swarms used during the 2018 Winter Olympics.
However, autonomous objects cannot replace the human brain and operate most effectively with a well-defined purpose.
Blockchain is a kind of distributed ledger, a chronologically ordered expanding list of irrevocable transactional records with cryptographic signature shared by all participants in a network.
The blockchain allows the parties to trace the plants and their origin, which is beneficial for traditional assets, but it also paves the way for other uses, such as tracing food-borne diseases to the original supplier. Furthermore, it allows 2 or more parties who do not know each other to interact safely in a digital environment and exchange value without the need for centralized authority.
The complete blockchain model includes 5 elements: a shared and distributed ledger, an immutable and traceable ledger, cryptography, tokenization and a distributed public consensus mechanism. However, the blockchain remains immature for corporate implementations due to a number of technical problems including poor scalability and interoperability.
In the future, the complete blockchain model will have the potential to transform industries and, finally, the economy, because complementary technologies such as AI and IoT will begin to integrate together with the blockchain. This expands the typology of participants and will include machines, which will be able to exchange a variety of assets - from money to real estate. For example, a car would be able to negotiate insurance prices directly with the insurance company based on the data collected by its sensors.
Blockchain, which is already appearing in experimental and small-scale projects, will be fully scalable by 2023.
Over the next 5 years, Artificial Intelligence, and in particular Machine Learning, will be applied to increase human decision-making through a wide range of use cases. At the same time, inevitably, there will be a huge increase in potential attack points with IoT, Cloud Computing, microservices and highly connected systems in smart spaces. Although this creates great opportunities by allowing hyper-automation and exploiting autonomous objects to achieve corporate transformation, new and significant challenges will also be created for the corporate security team.
Below we list the 3 main themes for the security of Artificial Intelligence: