AI and automation
Let's discuss your project →Should a Small Team Delegate Its Weekly Operations Review to ChatGPT Work?
A practical way to decide whether a small team should delegate a weekly operations review to AI, with governance, permissions, a pilot template, and service links.
Learn more →AI or traditional automation: how to choose your first business project
A practical framework for choosing a first automation project: rules, human-reviewed AI, or manual handling, with a simulated admin-request case.
Learn more →AI agents at work: what to assess before delegating business processes | Dedaloop
OpenAI describes growing use of agents such as Codex for longer and cross-functional tasks. For organizations, the issue is not adopting a new chatbot, but redesigning processes, permissions, controls and metrics.
Learn more →ChatGPT in healthcare: what the AdventHealth case teaches about AI adoption in regulated environments | Dedaloop
OpenAI describes how AdventHealth is using ChatGPT for Healthcare to reduce administrative work and improve workflows. The operational lesson: without governance, measurement and process redesign, AI remains an isolated pilot.
Learn more →From search engine to conversation: what the Omio case teaches about AI in digital products | Dedaloop
The Omio/OpenAI case shows how conversational agents can enter digital services and internal workflows. An operational reading for organizations assessing AI, automation and governance.
Learn more →OpenAI’s Bio Bug Bounty: Lessons for Enterprise AI Security and Governance | Dedaloop
OpenAI launches a red teaming challenge focused on bio-related risks: applications close on June 22, 2026, testing runs until July 27, and the top reward is up to $25,000. An operational read for AI governance in business.
Learn more →Codex Plugins and Skills: The Operational Lesson for Enterprise AI Workflows | Dedaloop
OpenAI Academy explains how Codex can use integrations and procedures to access tools, data and repeatable workflows. For businesses, the key is deciding when to connect external sources and when to formalize a process.
Learn more →AI and advanced research: what the OpenAI case teaches about validating results | Dedaloop
An OpenAI model reportedly disproved a long-standing conjecture in discrete geometry. For organisations, the point is not to celebrate autonomous AI, but to understand how to validate complex results generated by advanced models.
Learn more →OpenAI for Singapore: what it teaches companies that want to scale AI | Dedaloop
The multi-year partnership announced by OpenAI in Singapore is a useful signal for companies and public organisations: generative AI does not scale through tools alone, but through governance, skills, data and security.
Learn more →OpenAI Privacy Filter: what it means for data protection in enterprise AI workflows | Dedaloop
OpenAI introduces Privacy Filter, an open-weight model to detect and mask PII in text. An operational read for AI, DevOps and governance teams.
Learn more →OpenAI Brings Shared Workspace Agents to ChatGPT: What Businesses Should Assess Before Adoption | Dedaloop
OpenAI’s new feature lets teams create Codex-based agents for complex workflows, with integrations, controls and approvals. An operational read for CIOs, IT leaders and digital teams.
Learn more →Shared standards for advanced AI: what changes for governance, audits and enterprise adoption | Dedaloop
OpenAI supports the creation of shared standards to evaluate and govern advanced AI systems. For companies and public bodies, the operational priority is to prepare verifiable evidence, controls and adoption criteria.
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