Gartner's Top 10 Tech Trends for 2024 | Full Keynote from #GartnerSym | Summary and Q&A

TL;DR

Gartner presents 10 AI and technology trends focused on protecting investment, empowering developers, and delivering value in various industries.

Key Insights

• 🏗️ The future is always under construction, and innovation takes time to evolve and mature.
• 🔐 Protecting investments in AI requires AI trism and continuous threat exposure management to address security, privacy, and ethical concerns.
• 🪛 Sustainability initiatives driven by data analytics and platform engineering can enhance digital maturity and resilience.
• 🈂️ Developer-driven self-service platforms and AI-augmented development increase productivity and creativity while standardizing processes.
• ☁️ Industry cloud platforms empower organizations to deliver value by leveraging industry-specific capabilities and reducing redundancy.
• 🈸 Optimizing decision-making with AI in intelligent applications and apps improves user experience and business outcomes.
• ❓ Generative AI has the potential to revolutionize various domains, but ethical considerations and robust architecture understanding are critical.
• 🈂️ Empowering the workforce with AI and data enhances problem-solving capabilities and improves service delivery.
• 💠 Machine customers will become more prevalent, requiring organizations to consider ethical and shaping factors in their interactions.

Transcript

great welcome welcome everybody Welcome to the peak of inflated expectations you feel it right you feel it and I don't mean that in a bad way right but but uh what happens after the peak of inflated expectations the trough of dis how many feel like you're already in it trough of disillusion meant right now what about the traa disol traa disillusion... Read More

Questions & Answers

Q: What is AI trism and how does it relate to protecting investments in AI?

AI trism refers to trust, risk, and security management for AI. This trend focuses on enhancing transparency, control, and explainability in AI systems to ensure the protection of investments in AI technology. It helps address security and privacy issues, as well as biases within AI models, to create a more robust and trustworthy AI environment.

Q: How can continuous threat exposure management help organizations protect themselves from emerging threats?

Continuous threat exposure management involves proactively assessing and managing an organization's attack surface and IT assets to detect vulnerabilities and mitigate risks. By regularly evaluating the business attack surface, discovering and prioritizing IT assets, and validating and mobilizing against threats, organizations can enhance their security posture and minimize the likelihood of breaches or cyber attacks.

Q: How does AI-augmented development impact software engineering and developer productivity?

AI-augmented development refers to the use of AI tools and platforms to enhance the productivity and creativity of software engineering teams. These tools assist developers in various tasks, such as generating code, suggesting architectural solutions, enhancing testing processes, and providing intelligent prompts. By leveraging AI in development, teams can streamline their workflows, reduce manual effort, and focus on more complex and innovative tasks, thereby improving overall productivity and retention of talent.

Q: What role do industry cloud platforms play in delivering value in specific industries?

Industry cloud platforms are specialized platforms tailored to meet the unique needs and regulations of specific industries. These platforms provide pre-built functionalities, data models, and compliance frameworks, enabling organizations to accelerate innovation, reduce redundancy, and achieve faster time to market. By leveraging industry cloud platforms, businesses can deliver value by leveraging industry-specific capabilities and integrating cross-functional systems seamlessly.

Q: What is AI trism and how does it relate to protecting investments in AI?

AI trism refers to trust, risk, and security management for AI. This trend focuses on enhancing transparency, control, and explainability in AI systems to ensure the protection of investments in AI technology. It helps address security and privacy issues, as well as biases within AI models, to create a more robust and trustworthy AI environment.

More Insights

• The future is always under construction, and innovation takes time to evolve and mature.

• Protecting investments in AI requires AI trism and continuous threat exposure management to address security, privacy, and ethical concerns.

• Sustainability initiatives driven by data analytics and platform engineering can enhance digital maturity and resilience.

• Developer-driven self-service platforms and AI-augmented development increase productivity and creativity while standardizing processes.

• Industry cloud platforms empower organizations to deliver value by leveraging industry-specific capabilities and reducing redundancy.

• Optimizing decision-making with AI in intelligent applications and apps improves user experience and business outcomes.

• Generative AI has the potential to revolutionize various domains, but ethical considerations and robust architecture understanding are critical.

• Empowering the workforce with AI and data enhances problem-solving capabilities and improves service delivery.

• Machine customers will become more prevalent, requiring organizations to consider ethical and shaping factors in their interactions.

• Building on these trends enables builders and developers to create innovative solutions and capitalize on emerging opportunities.

Summary & Key Takeaways

• The content discusses the rise of AI and technology trends after the peak of inflated expectations and emphasizes the importance of moving from experimentation to scaled production.

• Gartner identifies 10 useful trends that can be implemented now, including AI trism for protection, continuous threat exposure management, sustainability initiatives, developer-driven self-service platforms, and AI-augmented development for improved productivity.

• The content also highlights the significance of industry cloud platforms, optimizing decision-making with AI, the potential of generative AI, empowering the workforce using AI and data, and the emergence of machine customers.