Artificial intelligence at work: 5 practical uses to get started
No hype: where AI already helps in a company’s day to day and how to start safely, using your own data.
· Josué Juca
- Five practical uses: support, summaries, reading documents, internal search and automation with decisions.
- Start with a repetitive, well-defined task, with a person reviewing the result.
- Watch sensitive data (LGPD), human review and integration with your systems.
Talking about artificial intelligence usually brings big promises and little practice. Here are five concrete uses that already work for companies of any size and do not require changing everything at once.
1. Customer support
An assistant can answer customers’ and teammates’ most frequent questions at any hour and hand over to a person when the topic is more delicate. The gain is freeing the team for the cases that really need them.
2. Summaries and reports
AI summarizes tickets, meetings and long documents and can draft a report from your data. Someone reviews and approves it, but the work of starting from scratch disappears.
3. Reading documents
Invoices, contracts and PDFs can have their data extracted automatically and sent to spreadsheets or systems instead of being typed by hand. That cuts errors and speeds up processes such as registration and checking.
4. Internal search
Manuals, policies and histories end up scattered across folders and emails. An assistant connected to those materials lets you ask in plain language and get an answer pointing to where it came from.
5. Automation with decisions
Combined with process automation, AI classifies emails and tickets, identifies the topic and triggers the right workflow, such as opening a task, replying to the customer or alerting the responsible team.
Once the gain from a first task is proven, it is easy to expand AI to other areas of the company.
Summing up the five uses and who should review the result:
| Use | Example | Who reviews |
|---|
| Support | Answering frequent questions | The team, on sensitive cases |
| Summaries and reports | Summarizing tickets and meetings | Whoever will use the summary |
| Reading documents | Extracting data from invoices and contracts | A checker, by sampling |
| Internal search | Asking about manuals and policies | Whoever maintains the documents |
| Automation with decisions | Classifying emails and tickets | The team, on exceptions |
Important precautions
- Sensitive data: know where your data goes and handle personal information according to LGPD.
- Human review: AI can be wrong or make things up, so check anything critical before using it.
- Integration: the value shows up when AI talks to your systems and data, not as an isolated tool.
- Measurement: compare time and quality before and after to know whether it is worth it.
How to start
Pick the process that bothers your team the most and talk to us. Together we evaluate whether AI is the best solution and how to integrate it safely with your systems.