Contents
As of July 2026, Samsung’s rollout of ChatGPT Enterprise and Codex to tens of thousands of employees shows AI moving from internal experiment to large-scale enterprise infrastructure, reshaping how content, cross-functional collaboration and campaign decisions are handled. For Vietnamese marketers, the deeper lesson is that businesses can only harness AI advertising effectively when scale is paired with risk controls, clear usage processes and proper employee training.
Samsung brings ChatGPT and Codex into global operations
OpenAI said Samsung Electronics is rolling out ChatGPT Enterprise and Codex to all Samsung Electronics employees in South Korea, while also making them available to all employees in the Device eXperience (DX) division worldwide. This is considered one of OpenAI’s largest enterprise deployments to date.
What stands out is that Samsung is not limiting AI to technical teams. According to OpenAI, the company plans to use ChatGPT and Codex across many areas of work, from software development, R&D, and manufacturing to marketing and office functions. This reflects how large enterprises are shifting AI from a personal productivity tool to shared productivity infrastructure.
For marketing in particular, this move shows that AI is increasingly seen as a tool to accelerate drafting, research, data synthesis, and campaign coordination across departments. However, deploying it at scale also requires businesses to standardize inputs, verify outputs, and clearly define which tasks may be automated.
Enterprise AI is spreading into advertising, not just coding
OpenAI said Codex was originally built for software development, but is gradually becoming useful for many other types of work. This is an important detail for the advertising industry, because it shows the line between tools “for technical work” and “for creative work” is becoming blurred.
In practice, advertising teams can use AI to:
- draft campaign content faster;
- summarize insights from multiple data sources;
- support ideation for multiple message variations;
- improve coordination between marketing, product, and operations;
- shorten the time from idea to execution.
However, these benefits only materialize when AI is placed within a controlled workflow. For major brands, speed cannot come at the expense of positioning mistakes, messaging errors, or brand inconsistency. Therefore, AI should be seen as a “productivity assistant,” not a machine that independently decides all advertising content.
Lessons from the AI wave: large-scale deployment must go hand in hand with risk management
According to the source data, OpenAI is also being mentioned in the context of launching a more capable version of its cybersecurity model. Although the second news site did not provide the full public content due to verification requirements, this detail still reinforces a familiar trend: as AI becomes more powerful, the need for security and oversight rises as well.
This is a point marketers should not overlook. Many businesses are using AI to create content, analyze customers, or support media planning, but still lack clear processes for data protection, access control, or usage guidelines. As AI becomes more deeply embedded in advertising operations, risks related to sensitive data, misinformation, or overreliance on tools will become more significant.
For brands considering investment in AI advertising, the lesson is this: the broader the deployment, the tighter the control standards must be. An AI system is only truly useful when the business clearly understands its intended use, the scope of data that may be entered, and the review mechanism before publication.
From AI trials to standardization in advertising and content
In Vietnam, many businesses have already started using AI for content creation, customer care, and advertising performance optimization, but most are still operating at a trial stage or relying on individual employees. Samsung’s story suggests the next phase may be one of “AI standardization” rather than simply “AI experimentation.”
For Vietnamese marketers, three priorities are worth considering:
- build rules for using AI in advertising and brand content;
- train teams to verify, edit, and control AI outputs;
- tie AI to clear business goals instead of chasing tool trends.
In other words, the real value of AI advertising is not in which tool you use, but in how the business organizes its workflow, manages data, and preserves brand identity while accelerating content production.
Source: OpenAI; Axios.
Explore more marketing analysis & guides at Marketing365.
Follow more updates from Marketing365 to stay on top of the latest marketing trends.
Read more articles in the Digital Trends category.
References
- Samsung Electronics brings ChatGPT and Codex to employees
- OpenAI rolls out more capable version of its cybersecurity model
