Google published a practical review of how its teams use artificial intelligence to save time, generate ideas, and improve everyday processes. Sound familiar? Many of these applications are already within reach of companies and professionals, not just large research labs. (blog.google)

The essentials of the news

The article, published by Google on August 18, 2025, lists 14 real cases inside the company where AI helps solve concrete tasks: from writing code to reducing food waste in their cafeterias. It’s an internal look to show that AI can be a work tool, not just a tech curiosity. (blog.google)

14 examples with direct impact

I’ll summarize the most relevant examples and why they matter if you work in a team or manage processes.

1. Generating code. Google says AI participates in about 30% of the new code their developers write, and engineers then review and approve that code. This changes how effort is distributed in a project. (blog.google)

2. Increasing development speed. Beyond writing lines, AI helps with reviews, testing, and migrations, with an estimated 10% impact on engineering velocity. Less time on repetitive tasks means more time for innovation. (blog.google)

3. Prioritizing and fixing bugs. Internal models help detect root causes and eliminate duplicates, letting teams focus work where it’s most needed. (blog.google)

4. Creative inspiration. Marketing and product teams use Gemini as a creative assistant to generate concepts, scripts, or variants aligned with brand style. Missing ideas? AI can speed up the first draft. Try Gemini. (blog.google)

5. YouTube content. Gemini helps extract quotes and timestamps from podcasts to optimize titles and descriptions, improving relevance and engagement. (blog.google)

6. Creating visual assets. At events like Google I/O, the company used generative models to produce hundreds of slides and a significant portion of videos. This shows AI already contributes to visual assets at scale. (blog.google)

7. Testing ideas quickly. Teams like DeepMind use creative tools to sketch videos or explore pitches without investing heavy resources up front. (blog.google)

8. Responding to business proposals faster. An internal system helped increase completed proposals by 78% year over year for Google Cloud, speeding commercial processes and reducing friction. (blog.google)

9. Improving lead quality. An AI-based filter increased conversion from leads to opportunities by 14% over a six-week period, helping prioritize sales efforts. (blog.google)

10. Meeting notes and summaries. During Google Meet calls, Gemini can transcribe and generate summaries with key points and tasks. Google reported that in a single month 50 million attendees benefited from AI-generated notes. This reduces the burden of taking notes during meetings. (blog.google)

11. Moderation and safety. Trust & Safety teams use AI to detect potential policy violations, speeding reviews and protecting platforms more efficiently. (blog.google)

12. Analyzing employee feedback. Tools like NotebookLM help summarize thousands of survey responses and extract common themes, speeding up internal decisions. If you don’t know NotebookLM, you can check it out here: NotebookLM. (blog.google)

13. Recruitment. AI supports sourcing and matching candidates to openings, always with recruiters leading the process to safeguard fairness and the final human decision. (blog.google)

14. Reducing food waste. By analyzing operational data, AI helped adjust menus and decreased waste per person in Google cafeterias by about 39% compared to 2019. This is a clear example of environmental and economic impact. (blog.google)

What does this mean for you and your team?

Worried that AI will replace jobs? Google’s narrative sums it up well: AI frees time from repetitive tasks and creates new functions and responsibilities. In practice, this translates into roles that combine human judgment with tools that boost productivity. (blog.google)

If you manage a team, think of concrete applications you can trial in short pilots of a few weeks. For example:

• Use AI to summarize meeting outcomes and save documentation time.
• Automate classification of bugs or tickets to prioritize the most critical items.
• Try generating creative drafts for campaigns and then challenge them with your human judgment.

Risks and good practices

The post also emphasizes that people remain in charge. That means internal policies for human review, security controls, and validation processes. Adopting the tool isn’t enough; you must integrate it with governance, verification, and transparency. (blog.google)

AI is a collaborative tool. Real value appears when people decide, validate, and guide the results.

Final reflection

The most interesting bits aren’t the flashy headlines but the practical details: efficiency percentages, concrete cases in sales, product, and operations. If you want to bring this to your organization, start small, measure results, and prioritize human oversight. AI is already transforming how we work. The question now is how you’ll adopt it to improve what you do today. (blog.google)