2022战略性技术趋势：12个塑造数字业务未来的趋势（英）-19页_164kb

报告摘要

Gartner® 2022 Top Strategic Technology Trends Summary

Core Content

Gartner's 2022 report outlines 12 strategic technology trends that are shaping the future of digital business. These trends are grouped into three categories: Engineering Trust, sculpting change, and Accelerating Growth, each focusing on different aspects of digital transformation and innovation.

The report emphasizes that IT leaders are crucial in enabling digital business success by leveraging these technologies to support growth, digitalization, and efficiency. It also highlights the need for collaboration between IT and business teams, referred to as "fusion teams," to drive innovation and adapt to the fast-paced digital landscape.

Main Trends and Key Information

1. Engineering Trust

Trends: Data Fabric, Cybersecurity Mesh, Privacy-Enhancing Computation, Cloud-Native Platforms
Key Points:
- Data Fabric: Integrates data across platforms and users, enabling efficient data utilization and reducing management tasks by up to 70%. By 2024, it will quadruple efficiency in data use.
- Cybersecurity Mesh: Provides a scalable and interoperable security framework based on identity. By 2024, organizations adopting this will reduce the financial impact of security incidents by 90%.
- Privacy-Enhancing Computation (PEC): Enables data sharing while preserving privacy through encryption, splitting, or preprocessing. By 2025, 60% of large organizations will use PEC techniques.
- Cloud-Native Platforms: Focus on cloud elasticity and scalability to deliver faster time to value. By 2025, over 95% of new digital initiatives will be built on cloud-native platforms.

2. Sculpting Change

Trends: Composable Applications, Decision Intelligence, Hyperautomation, AI Engineering
Key Points:
- Composable Applications: Built from reusable modules (PBCs), allowing fusion teams to create applications rapidly. By 2024, the design mantra for new applications will be "composable API-first or API-only."
- Decision Intelligence: Uses frameworks to model and improve decisions. By 2023, over a third of large organizations will have analysts practicing decision intelligence.
- Hyperautomation: Combines multiple technologies to automate business and IT processes. By 2024, hyperautomation spending will increase the total cost of ownership 40-fold, emphasizing the need for adaptive governance.
- AI Engineering: Focuses on operationalizing AI models with integrated pipelines and governance. By 2025, enterprises with AI engineering best practices will generate three times more value from AI than those without.

3. Accelerating Growth

Trends: Distributed Enterprise, Total Experience, Autonomic Systems, Generative AI
Key Points:
- Distributed Enterprise: A remote-first and virtual-first approach to digitize consumer touchpoints. By 2023, 75% of organizations using distributed enterprise will grow revenue 25% faster than competitors.
- Total Experience: Unifies customer, user, employee, and multiexperience to create a holistic stakeholder experience. By 2026, 60% of large enterprises will use total experience to enhance customer and employee advocacy.
- Autonomic Systems: Self-managing systems that dynamically adapt to environments without software updates. By 2024, 20% of organizations selling autonomic systems will require customers to waive indemnity provisions.
- Generative AI: Creates new, original artifacts from training data, enabling rapid innovation. By 2025, generative AI will account for 10% of all data produced, up from less than 1% today.

Key Takeaways

These trends are interdependent and collectively support the CEO's priorities of growth, digitalization, and efficiency.
IT leaders are encouraged to adopt a strategic approach, focusing on trust, collaboration, and innovation.
Early adoption and investment in these technologies can provide a competitive advantage.
Fusion teams are essential in driving digital transformation and should be supported with the right tools and practices.

How to Get Started

Data Fabric: Use metadata analytics to identify priority areas for data integration.
Cybersecurity Mesh: Prioritize composability and interoperability in security solutions.
Privacy-Enhancing Computation: Investigate key use cases for PEC and prioritize relevant techniques.
Cloud-Native Platforms: Avoid lift-and-shift migrations and invest in modern application architecture.
Composable Applications: Champion composable principles in new initiatives and use standard PBCs.
Decision Intelligence: Apply it to areas requiring data-driven or AI-powered decision support.
Hyperautomation: Establish holistic mapping and prioritization of initiatives for coordinated outcomes.
AI Engineering: Implement best practices from DataOps, ModelOps, and DevOps to maintain AI value.
Distributed Enterprise: Pivot business models to a "virtual first, remote first" approach.
Total Experience: Encourage cross-functional collaboration and ensure leaders are accountable for stakeholder experience.
Autonomic Systems: Pilot autonomic technologies in complex systems for agility and performance.
Generative AI: Accelerate content and R&D by leveraging proven use cases and enhancing personalization.