Generative AI in startups: real-world applications

Generative artificial intelligence has, in just a few years, gone from being an experimental technology to becoming an everyday tool for thousands of startups. According to the 2025 Entrepreneurship Map, produced by South Summit and IE University, more than half of Spanish startups already use it on a regular basis. Spain has also established itself as one of Europe’s leading ecosystems for the development of and investment in artificial intelligence.
However, the real impact of this technology is not in spectacular demos or in headlines about the future. It lies in how it helps entrepreneurial teams work smarter and more efficiently: speeding up product development, automating repetitive tasks, improving customer relationships, or making better-informed decisions.

The question is no longer whether to use generative AI, but where it can add the most value to the project. Here are some of the applications that are already transforming the day-to-day operations of startups.

Product and development: building faster with small teams

For a startup, speed is a decisive factor. Validating an idea before the competition, launching new features, or fixing bugs quickly can make the difference between growing and falling behind.

In this context, generative AI tools are transforming the way products are built. Coding assistants no longer just suggest lines of code; they help generate complete features, identify bugs, create automated tests, or document technical processes.

Tools like Claude Code, Codex, or Cursor enable tech teams to move faster on tasks that previously required many hours of manual work. They are complemented by specialized code-review solutions such as CodeRabbit or Greptile, which can detect issues, suggest improvements, and strengthen software quality before deployment to production.

For many startups, especially in their early stages, these tools represent a significant advantage. They allow small teams to build more product with the same resources, reduce delivery times, and devote more effort to innovation and less to repetitive, low–value-added tasks.

Operations: automating the invisible work

A large share of a startup’s time is spent on operational and administrative tasks that, while necessary, provide little differentiation. Email management, document classification, incident tracking, or searching for information are common examples.

Generative AI is making it possible to automate an ever-growing portion of these processes, freeing up time for higher-impact activities.

One of the most widespread use cases is intelligent email management. Agents can classify messages, identify recurring requests, extract relevant information from attached documents, and prepare draft replies for review. Integration tools such as Composio also make it easier to connect these agents with existing business applications and workflows.

These capabilities are also being applied to monitoring technical incidents and compiling information from multiple corporate tools. The result is automatic, contextualized summaries that reduce analysis time and enable faster decision-making.

Another area with great potential is knowledge management. Tools like NotebookLM, based on Google’s Gemini models, allow teams to query internal documentation, reports, or procedures using natural language, turning scattered information into accessible knowledge for the whole team.

The result is clear: less time spent searching for information, coordinating tasks, or managing administrative processes, and more time focused on the activities that drive innovation, productivity, and business growth.

Marketing and acquisition: reaching more customers with fewer resources

Creating content for social media, blogs, or advertising campaigns is probably one of the best-known uses of generative AI. Multimodal models such as Gemini can generate images, presentations, and marketing materials in minutes, while platforms like NotebookLM help turn market research, customer interviews, and other information sources into reports, summaries, and actionable briefs.

In the audiovisual space, tools like ElevenLabs make it possible to create voiceovers and dubbing in multiple languages with a high level of quality, enabling content adaptation and internationalization without major investment.

AI is also taking on an increasingly important role in sales prospecting. Some solutions help identify potential customers based on public signals, detect market opportunities, prioritize contacts with a higher likelihood of conversion, and generate personalized sales proposals.

For startups with limited resources, these capabilities represent a significant opportunity to increase visibility, expand commercial reach, and generate more opportunities without proportionally increasing costs.

Customer service: faster, more personalized experiences

Customer service is another area where generative AI is creating a tangible, measurable impact.

Today’s conversational agents can answer frequently asked questions, resolve simple issues, and provide support across multiple channels. Voice platforms such as ElevenLabs also make it possible to deploy agents that can interact naturally via phone calls or messaging apps, expanding support capacity without increasing the resources dedicated to customer care. 

To maximize their usefulness, these systems are often combined with techniques such as RAG (Retrieval-Augmented Generation), which allows them to respond using the company’s own documentation and knowledge. This is complemented by control mechanisms known as guardrails, designed to set boundaries, improve response consistency, and reduce operational risks.

A standout example in the Spanish ecosystem is Tucuvi, whose AI-based virtual nurse follows up with patients for different healthcare services under professional supervision, showing how these systems can deliver value in particularly demanding environments.

Experience shows that the best results are achieved when AI complements human work. Technology can handle routine inquiries and low-complexity tasks, while professionals focus on cases that require judgment, empathy, or specialized intervention.

Why is it especially useful for a startup?

Unlike large companies, startups usually operate with small teams, limited resources, and constant pressure to grow and execute quickly.

In this context, generative AI acts as an additional capability that amplifies the impact of each team member. It is not about replacing roles, but about freeing up time from repetitive, low-value work so more time can be dedicated to strategic activities such as innovation, product development, sales, or customer relationships.

A startup that manages to save several hours per person per week can translate that into a real competitive advantage: launching new products or features ahead of competitors, improving the user experience, accelerating customer acquisition, or exploring new business opportunities.

That is why the true value of AI is not measured by the number of tools implemented, but by its ability to solve specific problems, increase team productivity, and generate tangible business results.

How to take the first steps with generative AI

For startups that are taking their first steps in this area, the most common recommendation is to start with simple processes that are easy to measure.

Some good practices include:

• Identify repetitive tasks that take a lot of time.
• Start with a single use case and evaluate the results.
• Carefully review privacy and data-handling policies.
• Measure the time saved or the productivity improvement achieved.
• Always keep human oversight in critical processes.

Adoption is usually more effective when approached as a continuous improvement process rather than as a radical transformation from day one.

The competitive advantage is in usage, not in technology

Generative AI will not build a successful company on its own. However, it is already helping thousands of startups develop products faster, optimize internal processes, improve customer acquisition, and deliver faster, more personalized experiences.

The technology is becoming increasingly accessible, and adoption continues to accelerate. Therefore, the competitive difference will not lie in who has access to these tools, but in who can integrate them effectively into their processes, products, and day-to-day decisions. 

Ultimately, the competitive advantage is not in using AI, but in applying it where it creates real impact. Organizations that can identify these use cases and turn them into tangible results will be better prepared to innovate, grow, and adapt in an increasingly dynamic environment.

In addition to exploring new tools and use cases, it is important to understand the regulatory framework that accompanies this technological transformation. If you want to go deeper into this topic, you can consult other content on the ONE Platform about artificial intelligence, such as Do you know the new Artificial Intelligence Law?, AI Act: how to turn regulation into a competitive advantage, or The European Artificial Intelligence Regulation moves forward: new obligations for businesses.

On the ONE Platform you will find more resources, guides, and practical content to help you take advantage of the opportunities offered by artificial intelligence and other key technologies for the growth of your startup.