Emerging Technologies and Digital Transformation
Emerging Technologies and Digital Transformation tests how new technology changes service delivery, risk, and operating models, not hype terminology.
Core rules
- Cloud models: IaaS provides infrastructure; PaaS provides a runtime platform; SaaS provides an application. Responsibility is shared: the provider secures the cloud, and the customer secures what it puts in it.
- Containers package applications and dependencies; orchestration manages scale. They do not remove patching, identity, or network controls.
- AI and ML need data quality, bias testing, explainability, human oversight, and monitoring for drift. Generative AI raises data leakage and intellectual-property risks.
- IoT and edge computing increase physical exposure and update challenges. Segment devices and inventory them.
- Digital transformation changes processes and roles. Adoption needs sponsorship, training, and measurable outcomes.
- Avoid lock-in through exit plans, data portability, and standards.
Worked example
A department wants a SaaS ticketing tool. Under shared responsibility, the vendor patches the application and runs the data center. The organization still owns account provisioning, role design, data classification, retention, integration security, and contract exit. Before approval, review SSO, audit logs, data location, backup and export, and deletion terms.
Traps
Do not say cloud moves all security to the provider. Do not pilot AI on regulated data without approval. Do not assume containerization equals security. Do not call a technology purchase transformation without process change. Do not ignore exit costs and data extraction.