For years, companies have accumulated vast amounts of information with the promise of making better decisions.
However, having more data does not always mean understanding it better.
The complexity of data ecosystems and the need for specialised technical knowledge continue to make it difficult for many organisations to access relevant information.
In the latest episode of Digital Talks by t2ó ONE, Esther Checa talks to Almudena Barreiro, mathematician and Data Scientist at The Next Digital Hub, about how conversational analytics is transforming the way people interact with data and the opportunities Artificial Intelligence creates to make knowledge more accessible across organisations.
🎧 What will you learn in this episode?
- What conversational analytics is and how it enables people to interact with data using natural language.
- How it can make information more accessible to people without technical expertise.
- The risks of relying on AI-generated answers and how potential errors can be reduced.
- Why traceability and human oversight remain essential.
- How to measure whether conversational Business Intelligence is generating real business value.
- The role traditional dashboards will play in a future where talking to data becomes increasingly common.
Access to data has traditionally been shaped by technical expertise. Getting an answer to a business question could involve finding the right information, understanding the structure of databases or relying on specialised teams to build a query or visualisation.
Conversational analytics introduces a new way of interacting with that information. Using natural language, someone can ask questions such as “Why did sales drop this month?” or “Which store generated the most sales?”. Artificial Intelligence then acts as a translation layer: it interprets the question, converts it into a language the database can understand and returns the result in a format that makes sense to the user.
This shift can help remove one of the biggest barriers surrounding data: accessibility. People who previously depended on technical teams to access certain information can begin exploring data more directly and incorporating it into their everyday decision-making.
But easier access also creates new challenges.
One of the main concerns is the level of trust we place in answers generated by Artificial Intelligence. These systems can present information clearly and convincingly, but confidence in the way an answer is expressed does not necessarily mean that the result is correct.
This is why traceability plays such an important role in conversational Business Intelligence. Every figure, chart or conclusion should be linked to a calculation performed using the available data. AI can help interpret and communicate the result, but organisations need to ensure that the information actually comes from the underlying database.
To reduce these risks, companies can introduce different validation mechanisms. Trusted KPIs can help verify whether results remain within expected ranges, while other models can act as an additional layer of oversight to review AI-generated responses.
Building a strong semantic layer is also particularly important. This provides the context the system needs to understand what each data point means and how different sources of information relate to one another. The better the context, the greater the system’s ability to interpret questions correctly and provide useful answers.
Conversational analytics also opens up new possibilities for communicating information. Artificial Intelligence can help transform a table full of figures into an explanation tailored to the person who needs to make a decision.
However, as Almudena Barreiro explains during the conversation, the goal should be to use these tools to “tell stories with data, not fairy tales.” Technology can help us explain reality more effectively, but human oversight remains essential to ensure that the interpretation accurately reflects what the data is actually showing.
Another challenge is measuring the true impact of these tools.
The value of conversational Business Intelligence should not be measured solely by the time saved on each query. It can also be assessed by looking at which departments that previously lacked direct access to data are now using it, the types of questions they are asking and whether having access to that information enables them to respond more quickly when a problem arises.
The real potential emerges when accessing data is no longer a process reserved for specialists and instead becomes a natural part of everyday work for more people across an organisation.
In the short term, traditional dashboards are unlikely to disappear. Certain complex analyses will continue to require specific visualisation tools. However, conversational analytics can become a new layer that complements these systems and allows people to explore information in a much more flexible way.
A layer integrated directly into everyday work tools, where anyone can ask a question in natural language and receive a contextualised answer exactly when they need it.
Because perhaps the next big leap in Business Intelligence will not be about having more data, but about enabling more people to understand it and use it to make better decisions.
If you want to understand how conversational analytics is changing our relationship with data and explore the opportunities created by AI-powered Business Intelligence, you can now listen to the full episode of Digital Talks by t2ó ONE on Spotify, Apple Podcasts, YouTube and iVoox.
If you enjoyed the episode and found it relevant to your business, don’t miss the rest of the series. Learn from some of the best minds in the industry!
