• Evaluate the business impact of emerging technologies
• Examine and explore potentially transformative technologies
• Strategize how to benefit from these technologies

These technologies are expected to greatly impact business and society over the next two to 10 years, and will especially enable CIOs and IT leaders to deliver on the promise of digital business transformation.

• AI simulation is the combined application of AI and simulation technologies to jointly develop AI agents and the simulated environments in which they can be trained, tested and sometimes deployed.
• Causal AI identifies and uses cause-and-effect relationships to go beyond correlation-based predictive models and toward AI systems that can prescribe actions more effectively and act more autonomously.
• Federated machine learning aims to train a machine learning algorithm without explicitly sharing data samples, enabling better privacy and security.
• Graph data science (GDS) is a discipline in which data science techniques are applied to graph data structures to identify behavioral characteristics that can be used to build predictive and prescriptive models.
• Neuro-symbolic AI is a form of composite AI that combines machine learning (ML) methods and symbolic systems to create more robust and trustworthy AI models.
• Reinforcement learning (RL) is a type of ML where the learning system receives training only in terms of positive feedback (rewards) and negative feedback (punishments).

• AI-augmented software engineering, the use of AI technologies and natural language processing (NLP) to help software engineers create, deliver and maintain applications.
• API-centric SaaS,  a cloud application service designed with programmatic request/reply or event-based interfaces (APIs) as the primary methods of access.
• GitOps, a type of closed-loop control system for cloud-native applications.
• Internal developer portals, which enable self-service discovery and access to resources in complex, cloud-native software development environments.
• Open-source program office (OSPO), the center of competency to build strategies for governing, managing, promoting and efficiently using open-source software (OSS) and open-source data or models.

• Augmented FinOps, which applies the traditional DevOps concepts of agility, continuous integration and deployment, and end-user feedback to financial governance, budgeting and cost optimization efforts.
• Cloud development environments (CDEs), providing remote, ready-to-use access to a cloud-hosted development environment with minimal effort for setup and configuration.
• Cloud sustainability, the use of cloud services to achieve sustainability benefits within economic, environmental and social systems.
• Cloud-native, which refers to something created to optimally leverage or implement cloud characteristics that are part of the original definition of cloud computing, and include capabilities delivered as a service.
• Cloud-out to edge, an architectural construct where a centrally managed cloud environment, typically a hyperscale cloud, provides cloud service capabilities that are extended to edge environments.
• WebAssembly (Wasm), a lightweight virtual-stack machine and binary code format designed to support secure, high-performance applications on webpages.

• Cybersecurity mesh architecture (CSMA), an emerging approach for architecting composable, distributed security controls that improve overall security effectiveness.
• Generative cybersecurity AI, which generates new derived versions of security-related and other relevant content, strategies, designs and methods by learning from large repositories of original source data.
• Homomorphic encryption (HE), which uses algorithms to enable computations with encrypted data and enables businesses to share data without compromising privacy.
• Postquantum cryptography (PQC), also called quantum-safe cryptography, algorithms designed to secure against both classical and quantum-computing attacks.