From augmented humans to autonomous objects, including edge computing and hyper-automation, all of these technologies have been evaluated within the structures that the firm refers to as intelligent spaces. Human-centered, a “smart space” is a physical environment in which people and technological systems interact in increasingly open, connected, coordinated, and intelligent ecosystems. This approach highlights one of the most critical aspects of the studied technology: its impact on customers, employees, business partners or other key groups.
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Hyper automation
Hyper automation is the combination of multiple machine learning systems, integrated software, and automation tools. Hyper automation refers not only to the toolkit’s breadth but also to all stages of actual automation: discover, analyze, design, automate, measure, monitor, and reassess. Understanding the set of automation mechanisms, how they are interconnected, and how they can be combined and coordinated is the main challenge of hyper automation.
This trend appeared with the automation of robotic processes (robotic process automation, RPA). Used alone, however, RPA does not achieve hyper-automation objectives, which require a combination of tools to replicate the different elements in which a human is involved.
Multi experience
By 2028, the user experience will undergo a significant change in how users perceive the digital world and how they interact with it. Virtual reality (VR), augmented reality (AR), and mixed reality (MR) is also changing how people relate to the digital world. This combined change in perception and interaction patterns will ultimately lead to a multisensory and multimodal experience.
According to Brian Burke, we will move from a model where humans must understand technologies to a universe where technologies must understand humans and anticipate their demands or their intentions. “This ability to communicate with users through most of the human senses will result in a richer environment that can provide much more nuanced information,”
Democratization of expertise
This democratization consists of giving as many people as possible access to technical expertise (machine learning, application development, etc.) or business expertise (sales process, economic analysis, etc.) through a radically simplified experience, without requiring any lengthy and expensive training. The Gartner researcher cited the example of citizen access (citizen data scientists, citizen integrators) and the expected evolution of citizen development and codeless models.
Gartner predicts that by 2023 we will see an acceleration in four critical aspects of this phenomenon: the democratization of data and analytics (by expanding the tools initially intended for data scientists to reach the professional community developers), the democratization of application development (AI tools to take advantage of custom-developed applications), the democratization of design (extension of the “code-free” phenomenon with the automation of additional development functions to enhance the citizen developer) and democratization of knowledge (by providing access to expert tools and systems that allow non-IT professionals to exploit and apply specialized skills beyond their own field of expertise).
The augmented human
Human augmentation is an area that explores ways to use technology to provide humans with cognitive and physical enhancements that are integral to the human experience. Physical augmentation improves the physical capacities of humans by wearing or implanting technological components. As for cognitive enhancement, it consists of accessing information and using applications through traditional computer systems and developing new multi-experience interfaces. In the next ten years, the combination of these two types of increases is expected to become widespread, creating a phenomenon of “consumerization,” where employees will seek to exploit or expand their “personal increases”
Transparency and traceability
Consumers are increasingly aware of the value of their personal information and demand more and more control over this information. For their part, companies are aware of the growing difficulty of securing and managing personal data. For their detail, governments are implementing increasingly stringent regulations to ensure this. Therefore, transparency and traceability are essential elements in meeting these needs for digital ethics and the protection of personal data.
According to Gartner, transparency and traceability refer to a set of behaviors, actions, technologies, and practices to meet regulatory requirements and preserve an ethical approach to the use of artificial intelligence. To implement adequate transparency and trust practices, organizations must focus their efforts on three areas: artificial intelligence and machine learning, personal data confidentiality, and the consideration of ethics from the start.
The breakthrough of edge computing
Edge computing is an IT topology in which the collection, storage, and processing of data are carried out as close as possible to sources, repositories, and information consumers. Edge computing aims to reduce latency and leverage the capabilities of edge systems.
“The current interest in edge computing stems in large part from the need for IOT systems to provide disconnected or distributed functionality to embedded systems in specific industries such as manufacturing or retail.” Brian Burke explained. “Edge computing will become a dominant factor in virtually every industry and for all use cases when this architecture benefits from more sophisticated and specialized resources as well as more storage capacity. Complex edge architectures involving robots, drones, autonomous vehicles, and other operational systems – will accelerate this change,” he said.
The distributed cloud
This type of cloud involves distributing public cloud services to different locations, with the public cloud provider taking responsibility for the operations, governance, updates, and evolution of the services. “The distributed cloud, which represents a significant change from the centralized model applied today by most public cloud services, is set to be a major new step for cloud computing,” commented the Gartner researcher. “By 2024, the majority of cloud computing service platforms will deliver services that run where they need to be,” he added.
Autonomous objects
Autonomous objects are physical devices that use AI to automate functions previously performed by humans. The most prominent forms of such items are robots, drones, and autonomous vehicles. Their automation goes beyond that provided by rigid programming models, and they harness AI to adopt advanced behaviors that interact more naturally with their environment and with humans. Autonomous objects will increasingly be deployed in uncontrolled public spaces as technology, regulation, and social acceptance evolve.
“In the future, we expect autonomous smart objects to hand over to a multitude of collaborative smart objects, with multiple devices working in concert, independently or with human participation,” said Brian Burke.
Block chain put into practice
Block chain has the potential to reshape the industry by ensuring trust, ensuring transparency, and enabling the exchange of values between different ecosystems, with the corollary of lower costs, reduced time to settle transactions, and improved cash flow. “The block chain remains too immature for enterprise-wide deployments, due to a host of technical issues, including poor scalability and limited interoperability. Despite these challenges, the potential for disruption and generation of block chain revenue is why companies need to start.
AI and security
Gartner believes that artificial intelligence and machine learning will facilitate human decision-making across various cases, creating opportunities for hyper-automation and autonomous objects, among others. However, this development will pose new security teams’ challenges due to the massive increase in potential attack points generated by IOT, cloud, micro services, and highly connected systems. For Brian Burke, CISOs and Risk Managers should focus on three key issues: the protection of artificial intelligence systems, the use of AI to strengthen security, and the anticipation of malicious use of the AI by attackers.
