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Artificial Intelligence (AI) is no longer exclusive to the technology team. Today, marketing, creative, content, and digital strategy teams must understand how AI works and what tools power it—especially if they want to stay relevant in an increasingly competitive ecosystem.
Although marketers don’t need to be engineers, understanding the tools used by those who develop Artificial Intelligence models can open the door to better strategic decisions, more effective integrations, and smoother collaboration with technical teams.
Based on an analysis of the Artificial Intelligence (AI) Job Market report by Statista, we share a practical guide to the tools, platforms, and APIs most used by AI engineers. And most importantly—how can this information help marketers?
According to DevSkiller—one of the core sources of Statista’s report—more than 15,000 AI engineers were evaluated between January and June 2024. Their skills were measured through practical tests, focusing on APIs, frameworks, cloud platforms, and automation tools.
This API allows developers to build custom assistants using OpenAI models, with the ability to integrate files, tools, databases, and complex conversational flows.
For marketers, this means:
This cloud-based platform combines data engineering with data science and AI. It is mainly used to:
Marketing departments with advanced technical teams can use Databricks to build intelligent dashboards, campaign forecasts, or predictive analyses of churn or conversion.
Tabnine is an AI programming assistant that suggests code lines similarly to GitHub Copilot. Its mastery by AI engineers signals a trend toward assisted productivity, which is already beginning to impact marketing.
In areas such as landing page development, programmatic campaigns, or email template creation, technical marketing can benefit from using these types of tools, especially when working closely with developers.
DALL·E, from OpenAI, is widely used in creative teams to:
AI engineers mastering DALL·E also means that marketers must understand how prompts work, generative visual styles, and the legal implications of using AI-generated images.
Both Gemini (formerly Bard) and Alexa are platforms for developing conversational experiences. In marketing, this enables:
With the growth of voice searches and the increase in connected devices, the conversational interface will be key in omnichannel marketing strategies.
Based on this overview, we can identify several practical conclusions:
It’s not about coding, but about understanding what each tool can do and how to leverage it to improve campaigns, processes, or experiences.
The fact that “data literacy” scored low (41.54) among engineers also indicates a knowledge gap that marketers can close to lead cross-functional collaboration.
Tools like ChatGPT, DALL·E, and Tabnine are as useful to creatives as they are to developers. The future of marketing lies in hybrid teams speaking the same language.
The AI Job Market study reveals a clear truth: AI engineers already use a sophisticated toolkit of APIs, platforms, and cloud environments. For marketing to evolve with them, there’s no need to become a programmer—but learning to integrate, propose, and collaborate from a strategic and creative mindset is essential.
Brands that train their teams in these tools—even at a user or strategic level—will be better prepared to design experiences, automate processes, and connect with their audiences at scale.
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