Applied Generative AI: Keys to Innovation in Tech, Industrial, and Logistics Companies [PRACTICAL GUIDE]

Generative artificial intelligence has emerged as one of the most promising technologies for transforming business processes, accelerating innovation, and democratizing access to advanced solutions without the need to program.

At La Lonja de la Innovación, we work to identify technological opportunities applicable to the business ecosystem around us: from tech startups to established entities in the logistics, port, or industrial sectors.

This guide provides an introductory and practical overview of generative AI, supported by content shared by experts like Raúl Castilla, a data engineer who recently delivered three technical sessions at the hub.

You can watch the first session where we covered topics such as the relationship between data and AI, or tools that can be used day-to-day. At the end of the article, we explain how to access the third workshop to learn about legal and ethical challenges, including questions such as: What are the risks associated with authoritarian uses of AI? What is the regulation required to ensure its implementation is safe and responsible?

What is generative AI?

It is a branch of artificial intelligence capable of creating new content from existing data: text, images, code, sound, or even virtual worlds. Unlike traditional AI, which classifies, predicts, or recommends, generative AI produces something new, opening the door to automating creative, documentary, operational, or interaction processes.

"Generative AI generates content. It doesn't just analyze or decide, but creates: text, images, code... That is the real paradigm shift." Raúl Bravo, data engineer.

Why is it relevant for your business?

Because many tasks that currently take up time, attention, and resources can be transformed. From generating technical reports to prototyping interfaces or automating operational documentation. Its adoption allows:

• Accelerating repetitive tasks (such as technical documentation or proposal generation).
• Reducing technical dependency in early product or business stages.
• Expanding creative capacity of small or multidisciplinary teams.
• Improving customer experience with personalized automation.

Immediate application in business processes

Below is a table with clear examples of how generative AI can be applied to business processes, including real companies working at La Lonja de la Innovación:

What tools are available?

Here are some of the solutions mentioned by Raúl Bravo during his training session, which are accessible to any company:

• ChatGPT / Gemini / Claude: natural text generation for proposals, emails, training, ideas...
• Fireflies.ai / Otter.ai: automatic summarization and transcription of meetings.
• Gamma.app: automatic presentation generation.
• Vercel v0: web interface creation using natural language.
• Heen / D-ID: realistic avatar generation for internal communication or customer service.

Are we ready to apply generative AI?

Technical checklist for companies

Objective: help technical or strategic teams assess whether they are ready to implement generative AI solutions.

Infrastructure and data

Which of these checks does your company meet?

☐ We have accessible structured data (CSV, CRM, ERP, sensors, forms, etc.)
For example, historical data from logistics operations or internal metrics of industrial processes.

☐ Our systems are already connected, or could easily connect, to open platforms (such as FIWARE).
FIWARE facilitates data interoperability for AI in port sectors, mobility, or energy efficiency.

☐ We store data securely and in compliance with regulations (e.g. GDPR).
It’s an essential prerequisite for any responsible AI use.

Process maturity

Which of these checks does your company meet?

☐ We identify repetitive tasks that could benefit from generative AI.
Example: automated generation of inspection reports in companies like Eon Sea or operational documentation in Kimun Tech.

☐ We have processes that require fast or scalable personalization.
Such as adapting technical proposals or generating presentations for clients with tools like Gamma.

☐ There is some prior automation (scripts, macros, dashboards).
This indicates a technical readiness to easily integrate generative solutions.

Innovation culture

Which of these checks does your company meet?

☐ Our team is open to trying technological tools if they bring direct value.
Essential for driving pilot projects without friction.

☐ We have profiles capable of leading pilots or collaborating on projects with a technical component.
Even if they do not code, they must understand the usage cycle of AI tools.

☐ We see value in personalization, rapid prototyping, or content generation.
Generative AI excels in these scenarios and can be applied cross-functionally.

Evaluation

• 7 or more affirmative answers → your organization is in an excellent position to activate a pilot with generative AI, even with limited internal resources.
• 4 to 6 affirmative answers → there is potential, but it is recommended to accompany it with external advice or applied training.
• 3 or fewer affirmative answers → it is advisable to start with inspirational cases, initial training, or an audit of processes and data.

If you found this exercise interesting, stay connected with the latest updates on the initiative through our social networks and don't miss the third workshop, which you can access exclusively through this link: Artificial Intelligence: Legal and ethical challenges.

In this last workshop, we delve deeper into the legal and ethical challenges posed by the design, development, and deployment of AI systems with Raúl Castilla Bravo, Data Engineer at BEONx, and Eduardo Ballesteros, Lawyer at Montero Aramburu & Gómez-Villares Atencia.