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2023 Gartner Hype Cycle





What is the Gartner hype cycle for 2023?


The Artificial Intelligence (AI) 2023 Gartner Hype Cycle recognises developments and methods that provide substantial, perhaps even transformative benefits while also resolving the drawbacks and dangers of finite systems.

 

Emergent AI


These innovations offer chances for long-term differentiation and higher labour productivity. several other emerging AI techniques provide enormous promise to improve digital consumer experiences, make better business decisions, and set yourself apart from the competition, even though generative AI offers a significant potential to enable competitive differentiation.


Other essential emerging technologies in AI include:

👉 AI simulation

👉 Causal AI

👉 Federated machine learning

👉 Graph data science (GDS)

👉Neuro-symbolic AI

👉Reinforcement learning (RL)

 

Developer experience (DevX)


Businesses are primarily focused on improving the developer experience by enhancing interactions between developers and various elements like tools, platforms, processes, and people. This involves a range of technologies aimed at attracting and retaining top engineering talent.


One such technology is the value stream management platform (VSMP), which aims to optimize end-to-end product delivery and business outcomes. VSMPs focus on data integration across all software delivery stages, aiming to enhance software product performance by maximizing cost, operating models, technology, and processes. Despite their potential, widespread adoption of value stream management platforms is anticipated to take around two to five years.



In the developer experience, other crucial technologies include:


💥 AI-augmented software engineering

💥 API-centric SaaS

💥 GitOps

💥 Internal developer portals

💥 Open-source program office (OSPO)

 

Pervasive cloud


These technologies are redefining cloud computing by incorporating edge computing, vertical integration, and industry-specific solutions. To extract the most value from cloud investments, automation, access to cloud-native tools, and proper governance are crucial.


Industry cloud platforms exemplify this trend by combining SaaS, PaaS, and IaaS services to provide comprehensive solutions tailored to specific industries. These platforms offer a variety of tools, including industry data management, packaged business capabilities, and composition tools, fostering adaptability in response to rapid changes. The widespread adoption of these platforms is predicted to take around five to ten years.



Other essential pervasive cloud technologies include:


🎯 Augmented FinOps

🎯 Cloud development environments (CDEs)

🎯 Cloud sustainability

🎯 Cloud-native

🎯 Cloud-out to edge

🎯 WebAssembly (Wasm)

 

Human-centric security and privacy


The technologies in this category are designed to help organizations enhance their resilience by implementing security and privacy programs that prioritize human well-being. These technologies facilitate the development of a culture of trust and awareness among different teams within enterprises, leading to more informed decision-making regarding shared risks.


One specific example is AI trust, risk, and security management (AI TRiSM), which exemplifies this human-centric approach. It ensures the reliability, fairness, and trustworthiness of AI models by offering solutions for interpretability, anomaly detection, data protection, and resistance against adversarial attacks. Achieving mainstream adoption of these technologies is expected to take two to five years.


Other essential human-centric security and privacy technologies include:


🎉 Cybersecurity mesh architecture (CSMA)

🎉 Generative cybersecurity AI

🎉 Homomorphic encryption (HE)

🎉 Postquantum cryptography (PQC)


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