Top 10 Strategic Technology Trends for 2024
Global spending on digital transformation is predicted to jump 20% annually to $1.8 trillion next year, according to Statista.
“CEOs know they must accelerate the adoption of digital business and are seeking more direct digital routes to connect with their customers,” says David Groombridge, VP Analyst, Gartner.
By 2026, generative AI will significantly alter 70% of the design and development effort for new web applications and mobile apps, According to Gartner.
By 2027, 80% of CIOs will have performance metrics tied to the sustainability of the IT organization.
Here are the Top 10 Strategic Technology Trends for 2024. These strategic technology trends will factor into business and technology decisions over the next three years
- AI Trust, Risk and Security Management (AI TRiSM)
- Continuous Threat Exposure Management (CTEM)
- Sustainable Technology
- Platform Engineering
- AI-Augmented Development
- Industry Cloud Platforms
- Intelligent Applications
- Democratized Generative AI
- Augmented Connected Workforce
- Machine Customers
Each of the trends relates to one or more key themes for business: protecting and preserving past and future investments, building the right solutions for the right stakeholders at the right time, and delivering value for the changing environment of both internal and external customers.
Here are the Strategic Technology Trends for 2023 that will impact enterprise strategies in the coming three years by enabling organizations to address four key priorities
- Digital Immune System
- Applied Observability
- AI Trust, Risk and Security Management (AI TRISM)
- Industry Cloud Platforms
- Platform Engineering
- Wireless-Value Realization
- Superapps
- Adaptive AI
- Metaverse
- Sustainable Technology
1. Digital Immune System
Digital Immune System creates an enhanced customer experience by combining multiple software engineering strategies to protect against risk. Through observability, automation, and extreme design and testing, it delivers resilient systems that mitigate operational and security risks.
2. Applied Observability
Applied Observability works from the data emitted by an organization, using AI to analyze and make recommendations, which allow an enterprise to make faster and more accurate future decisions. When applied systematically, it can reduce the latency for response and optimize business operations in real time.
3. AI Trust, Risk and Security Management (AI TRISM)
AI TRiSM supports AI model governance, trustworthiness, fairness, reliability, robustness, efficacy and data protection. It combines methods for explaining AI results, rapidly deploying new models, actively managing AI security, and controls for privacy and ethics issues.
4. Industry Cloud Platforms
Industry Cloud Platforms combine SaaS, PaaS and IaaS with tailored, industry-specific functionality that organizations can use to more easily adapt to the relentless stream of disruptions in their industry.
5. Platform Engineering
Platform Engineering provides a curated set of tools, capabilities and processes that are packaged for easy consumption by developers and end users. It will increase end users’ productivity and reduce the burden on development teams.
6. Wireless-Value Realization
Wireless-Value Realization covers the provision of wireless network services from everything, including traditional end-user computing, support for edge devices, digital tagging solutions, etc. Such networks, including Enterprise Wi-Fi, go well beyond pure connectivity, providing location and other real-time information and insight from analytics, and allow systems to harvest network energy directly.
7. Superapps
Superapps are more than composite applications that aggregate services. A superapp combines the features of an app, a platform and an ecosystem in one application, providing a platform for third parties to develop and publish their own miniapps on.
Here are the examples Best Super Apps in the world
- Alipay
- OMNi
- Revolut
- PhonePe
- Rappi
- Grab
- Tata Neu
- Troop Messenger
- Gojek
- Clap Messenger
8. Adaptive AI
Adaptive AI allows for model behavior change post-deployment by using real-time feedback, to continuously retrain models and learn within runtime and development environments, based on new data and adjusted goals, to adapt quickly to changing real-world circumstances.
9. Metaverse
Metaverse allows people to replicate or enhance their physical activities. This could happen by transporting or extending physical activities to a virtual world or by transforming the physical one. It is a combinatorial innovation made up of multiple technology themes and capabilities.
10. Sustainable Technology
Delivering technology alone will not be enough in 2023. Sustainable technology is a framework of solutions that increases the energy and efficiency of IT services; enables enterprise sustainability through technologies like traceability, analytics, emissions management software and AI; and helps customers achieve their own sustainability objectives.
Investments in sustainable technology also have the potential to create greater operational resiliency and financial performance, while providing new avenues for growth. Via Gartner
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Her are the 12 strategic technology trends in 2022 to act as enhancers of digital business and innovation over the next 3 to 5 years, According Gartner.
- Data Fabric
- Cybersecurity Mesh.
- Privacy-Enhancing Computation.
- Cloud-Native Platforms.
- Composable Applications.
- Decision Intelligence.
- Hyperautomation.
- AI Engineering.
- Distributed Enterprises
- Total Experience – TX
- Autonomic Systems
- Generative AI
1: Data Fabric
Data fabric provides a flexible, resilient integration of data sources across platforms and business users, making data available everywhere it’s needed regardless where the data lives.
Data fabric can use analytics to learn and actively recommend where data should be used and changed. This can reduce data management efforts by up to 70%.
2: Cybersecurity Mesh
Cybersecurity mesh is a flexible, composable architecture that integrates widely distributed and disparate security services.
Cybersecurity mesh enables best-of-breed, stand-alone security solutions to work together to improve overall security while moving control points closer to the assets they’re designed to protect. It can quickly and reliably verify identity, context and policy adherence across cloud and noncloud environments.
3: Privacy-Enhancing Computation
Privacy-enhancing computation secures the processing of personal data in untrusted environments — which is increasingly critical due to evolving privacy and data protection laws as well as growing consumer concerns.
Privacy-enhancing computation utilizes a variety of privacy-protection techniques to allow value to be extracted from data while still meeting compliance requirements.
4: Cloud-Native Platforms
Cloud-native platforms are technologies that allow you to build new application architectures that are resilient, elastic and agile — enabling you to respond to rapid digital change.
Cloud-native platforms improve on the traditional lift-and-shift approach to cloud, which fails to take advantage of the benefits of cloud and adds complexity to maintenance.
5: Composable Applications
Composable applications are built from business-centric modular components. Composable applications make it easier to use and reuse code, accelerating the time to market for new software solutions and releasing enterprise value.
6: Decision Intelligence
Decision intelligence is a practical approach to improve organizational decision making. It models each decision as a set of processes, using intelligence and analytics to inform, learn from and refine decisions.
Decision intelligence can support and enhance human decision making and, potentially, automate it through the use of augmented analytics, simulations and AI.
7: Hyperautomation
Hyperautomation is a disciplined, business-driven approach to rapidly identify, vet and automate as many business and IT processes as possible. Hyperautomation enables scalability, remote operation and business model disruption.
8: AI Engineering
AI engineering automates updates to data, models and applications to streamline AI delivery.
Combined with strong AI governance, AI engineering will operationalize the delivery of AI to ensure its ongoing business value.
9: Distributed Enterprises
Distributed enterprises reflect a digital-first, remote-first business model to improve employee experiences, digitalize consumer and partner touchpoints, and build out product experiences.
10: Total Experience -TX
Total experience is a business strategy that integrates employee experience, customer experience, user experience and multiexperience across multiple touchpoints to accelerate growth. Total experience can drive greater customer and employee confidence, satisfaction, loyalty and advocacy through holistic management of stakeholder experiences.
11: Autonomic Systems
Autonomic systems are self-managed physical or software systems that learn from their environments and dynamically modify their own algorithms in real time to optimize their behavior in complex ecosystems.
12: Generative AI
Generative AI learns about artifacts from data, and generates innovative new creations that are similar to the original but doesn’t repeat it. Generative AI has the potential to create new forms of creative content, such as video, and accelerate R&D cycles in fields ranging from medicine to product creation. Via Gartner