Peak of Inflated Expectations and Beyond: Key Technology Trends

Jul 17, 2024

Lecture Notes: Peak of Inflated Expectations and Beyond

Introduction

  • Peak of Inflated Expectations: A phase where enthusiasm and hype are at their highest.
  • Trough of Disillusionment: The phase following the peak where the initial excitement wanes, but real work begins.
  • Key point: Lots of experiments and pilots, but little large-scale production yet.

Historical Example: Südbahn Railway (1848)

  • Built a complex railway through the Semmering Pass.
  • Initially, locomotives couldn't handle the gradients and curves.
  • Solution: Ran a competition for better locomotives.
  • Lesson: Vision and sticking with it are crucial, even if initial conditions are uncertain.

Vision and Innovation

  • Total Experience: Combines immersive experience and multi-experience to engage employees and customers.
  • Generative AI (Gen AI): Arrival from human augmentation, AI engineering, machine learning, and adaptive AI.
  • History: First mentioned in Gartner's research in August 2017.
  • Cloud Platforms: Continuous evolution from distributed cloud to industry cloud platforms.

Major Themes for Technology Trends

  1. Protecting Investment
  2. Rise of Builders
  3. Delivering Value

Protecting Investment

AI as a Partner

  • AI TRiSM: Trust, Risk, and Security Management.
  • Generative AI introduces new attack surfaces.
  • AI governance policies are crucial for transparency, control, and explainability.

Continuous Threat Exposure Management

  • Assessing business attack surfaces regularly.
  • Prioritizing critical assets for protection.
  • Utilizing AI to identify threat patterns.
  • More agile organizations tend to be three times less likely to suffer breaches.

Protecting the Future

  • Sustainability: Goes beyond 'green IT' to include engineering and power regulation.
  • Increases in digital maturity and resilience (86% see it as beneficial).
  • Future trend: 75% of CIOs will be responsible for tech solutions tied to sustainability.
  • ESG (Environmental, Social, Governance) demands rising, especially for AI model footprints.

Rise of Builders

Developer-Driven Self-Service

  • Platform Engineering: Standardizes functionalities across the organization.
  • Improves developer experience by reducing cognitive load and complexity.
  • Shifts from project management to product management.

AI-Augmented Development

  • Tools like Codex and GitHub Copilot.
  • Increases productivity in design, development, and testing.
  • Potential for language conversion (e.g., COBOL to Python).
  • Future potential in understanding architectures.

Industry Cloud Platforms

  • Encapsulate industry-specific regulations and data models.
  • Aim to shorten the timeframe to achieve business value.
  • Emerging trend in integrating generative AI into industry cloud platforms.

Delivering Value

Optimizing Decision-Making

  • AI embedding in enterprise applications for better forecasting and analysis.
  • Caution against locking into single-vendor AI workbenches.

Generative AI Everywhere

  • Significant interest across multiple modalities beyond text.
  • By 2030, every dollar of IT spend will include an AI component.
  • Encourages beyond productivity gains to core business improvements.

Empowering the Workforce

  • Real-time, data-driven problem solving using generative AI.
  • Improves employee experience and operational efficiency.
  • Use of Knowledge Graphs for better data retrieval.

Machine Customers

  • Increasing presence of AI-driven customers making data-driven decisions.
  • Ethical considerations and ESG promises will matter in business interactions.

Conclusion

  • These trends offer opportunities for innovation and problem-solving.
  • Focus on building something new and applicable for real-world scenarios.

Key phrase: "The future is always under construction."