The business magazine presents an overview of 12 strategic technology trends for the next 5 years. Why they are so important today for society and business. First of all, trends and innovations represent fundamental technical capabilities that everyone (both companies and specialists) needs to compete in the digital world.
These technology trends will drive digital business and innovation over the next 5 years through 2027, according to business analyst forecasts and research.
Content:
AI engineering
AI engineering automates the updating of data, models, and applications to optimize AI delivery. When combined with robust AI governance, AI engineering will enable AI adoption to ensure its continued business value.
As companies continue to innovate in AI, they also need to leverage all their resources—data, models, and compute.
Companies should consider ModelOps for implementing AI solutions. ModelOps reduces the time it takes to move AI models from pilot to production with a principled approach that can help ensure a high success rate. It also offers a system for managing and managing the lifecycle of all AI (graphic, linguistic, rule-based, and other decision models).
Data Fabric
Data Factory enables flexible and resilient integration of data sources across platforms and business users, making data available wherever it is needed, no matter where it is.
Data Fabric is the continuous analysis of existing, discovered, and prospective metadata assets to support the design, deployment, and consumption of integrated and reusable data across all environments, including hybrid and multi-cloud platforms.
Data Fabric can use analytics to learn and proactively recommend where data should be used and changed. This can reduce data management efforts by up to 70%.
A data factory uses both human and machine capabilities to access data in place or support its consolidation where needed. It continuously identifies and connects data from disparate applications to discover unique, business-critical relationships between available data points.
Cybersecurity Network
The Cybersecurity Network is a modern conceptual approach to security architecture that enables the distributed enterprise to deploy and extend security where it is needed most. The network is a flexible, composable architecture that integrates widely distributed and disparate security services.
In 2024, companies that implement a mesh cybersecurity architecture will reduce the financial impact of security incidents by an average of 90%. Companies now support multiple technologies in different locations, so they need a flexible security solution.
The network extends identities beyond the traditional security perimeter and creates a holistic view of the organization. It also helps improve the security of remote work. These requirements will drive adoption over the next few years.
The cybersecurity network enables best-in-class autonomous security solutions to work together to improve overall security while moving control points closer to the assets they are designed to protect. It can quickly and reliably verify identity, context, and policy compliance across cloud and non-cloud environments.
Privacy-enhancing computing
Privacy-enhancing computing methods: These technologies protect data while it is in use—as opposed to when it is at rest or in motion—enabling secure data processing, sharing, cross-border transfer, and analytics, even in untrusted environments.
Privacy-enhancing computing uses a variety of privacy-protecting techniques to extract value from data while meeting regulatory requirements.
This technology is rapidly transforming from academic research into real-world projects that deliver real value, opening up new forms of computing and sharing with reduced risk of data leakage.
Cloud platforms
Cloud platforms are technologies that enable new, resilient, elastic, and flexible application architectures that can respond to rapid digital change. Cloud platforms improve on the traditional piecemeal approach to the cloud, which fails to take advantage of the cloud and adds complexity to maintenance.
Cloud Native Application Protection Platforms (CNAPPs)
CNAPPs bring together multiple cloud security tools and data sources, including container scanning, cloud security posture management, infrastructure as code scanning, cloud infrastructure rights management, and runtime cloud workload protection platforms.
Secure Access Service Edge (SASE)
SASE is delivered as a service and provides access to systems based on device or object identity combined with real-time context and security and compliance policies.
SASE provides several converged network and security capabilities, such as SD-WAN and zero-trust network access (ZTNA). It also supports branch offices, remote workers, and general on-premises internet security.
Security Service Edge (SSE)
SSE protects access to the network, cloud services, and private applications. Capabilities include access control, threat protection, data security, security monitoring, and acceptable use controls, all delivered through network-based and API integration.
Composite applications
Composite applications are built from modular, business-focused components. Composite applications simplify the use and reuse of code, accelerating the time to market of new software solutions and increasing enterprise value.
Traditional digital AI models have limited adaptability because they cannot generalize beyond the data they were trained on. PIAI creates a more robust representation of the context and physical product. (PIAI) is an AI that can create physically and scientifically sound AI models. PIAI has attracted particular interest as a more effective option for modeling complex systems such as climate and environmental issues that are difficult to model given their scale.
The pandemic crisis has exposed the vulnerabilities of overly brittle business models. PIAI creates a more flexible representation of the context and conditions in which systems operate, allowing developers to create more adaptive systems. It can also create more robust and adaptable business modeling systems that are more robust across a wider range of scenarios.
Other emerging technologies in this area include composite applications, composite networks, and influence engineering.
Intelligence in decision making
Decision intelligence is a practical approach to improving organizational decision making. It models every decision as a set of processes, using intelligence and analytics to inform, learn, and refine decisions.
An intelligent decision-making system can support and improve human decision-making and possibly automate it through the use of advanced analytics, modeling, and artificial intelligence.
Hyperautomation
Hyperautomation is a disciplined, business-focused approach to quickly identify, validate, and automate as many business and IT processes as possible. Hyperautomation enables scalability, remote work, and business model disruption.
Hyperautomation involves the coordinated use of multiple technologies, tools or platforms, including:
- Artificial Intelligence (AI)
- Machine learning
- Event-driven software architecture
- Robotic Process Automation (RPA)
- Business Process Management (BPM) and Intelligent Business Process Management (iBPMS) suites
- Integration Platform as a Service (iPaaS)
- Open Source / No Code Tools
- Packaged software
- Other types of tools for automating decisions, processes and tasks
Distributed Enterprises
Distributed enterprises reflect a digital-first, remote-first business model to improve employee engagement, digitize consumer and partner touchpoints, and improve product experiences.
Distributed businesses are better positioned to serve the needs of remote workers and consumers, who are fueling demand for virtual services and hybrid workplaces.
General experience
Shared experience is a business strategy that connects employee experience, customer experience, user experience, and multi-user experience across multiple touchpoints to accelerate growth.
Shared experience can enhance trust, satisfaction, loyalty and support for customers and employees by holistically managing the stakeholder experience.
Autonomous systems
Autonomous systems are self-governing physical or software systems that learn from their environments and dynamically change their own algorithms in real time to optimize their behavior in complex ecosystems.
Autonomous systems create a flexible set of technological capabilities that can support new requirements and situations, optimize performance, and defend against attacks without human intervention.
Generative AI
Generative AI learns about artifacts from data and creates new innovative creations that are similar to the original but not identical. Generative AI can create new forms of creative content, such as video, and speed up research and development cycles in fields ranging from medicine to product design.
Organizations can use generative AI, which creates original media content, synthetic data, and models of physical objects. For example, generative AI was used to create a drug to treat obsessive-compulsive disorder (OCD) in less than 12 months.
Tech trends drive digital business
The top strategic technology trends will accelerate digital capabilities and drive growth by addressing common business challenges for CIOs and technology leaders. They offer a roadmap to differentiate your organization from competitors, achieve business goals, and position CIOs and IT leaders as strategic partners within the organization.
Each produces one of three main results:
Engineered Trust : Technologies in this segment create a more resilient and efficient IT foundation by enabling more secure integration and processing of data across cloud and non-cloud environments to enable cost-effective scaling of the IT foundation.
Sculpting Change : By releasing new creative technology solutions in this space, you can scale and accelerate your organization’s digitalization. These technology trends allow you to respond to the increasing pace of change by creating applications faster to automate business activities, optimize artificial intelligence (AI), and provide faster, smarter decisions.
