Over the last decade, generative AI has become much more accessible and is starting to attract the interest of many companies. This evolution has been made possible by the proliferation of open source tools, improvements in computing, and a further migration to the cloud.

But let’s start from the beginning.

What is generative AI?

Generative AI is a type of artificial intelligence that creates new content—such as text, images, audio, or code—by learning patterns from existing data and generating outputs that resemble human-created work.

At Narrativa, we have developed Narrativa® Navigator, a platform dedicated to providing generative AI solutions, capable of generating 3,000 mobile descriptions in seconds for Phone House, creating financial insights with WSJ, or writing a clinical paper in two simple steps for Pfizer, LLS, and many more.

How does all of this translate into value for companies?

Bloomberg and Morgan Stanley, success stories

At a meeting on innovation, Royal Bank of Canada Director Kim Prado was asked to name a trend that had the potential to bring the greatest value to their business in the next five years. She replied, “Without question it will be taking generative to the next level.”

If we believe that generative is the future, then this may very well be true. We are already seeing examples of success in some of the most well-known companies in the world, but there are still a few more steps needed to be able, as Prado says, to take generative AI to the next level.

Financial outlets like Bloomberg use generative AI to generate up to four types of automated news. Ted Merz, Director of News Product at the company, provides a significant statistic: readers of AI-generated news have increased from zero to 7% in the last two to three years. With this in mind, it is more than likely that at some point we have read an article generated by artificial intelligence without even realizing it.

The investment company Liquidnet creates personalized financial alerts for each client. Generative AI is initially used as a ‘library’ that includes bank records, public information, press releases, etc. It then converts this data into alerts written in natural language and sends them out by email.

The experience could not have been better. Here’s what Liquidnet CEO Tony Doris says: “It’s easier for us to do the job of converting content to generative AI text than it is for each of our users to interpret graphs, data tables and numbers. It’s just a more efficient way of communicating content to humans.”

Another area in which generative AI is proving disruptive is the field of internal communication. At Morgan Stanley, they have used this technology to create a chatbot to answer questions from employees. And they don’t plan to stop there, with plans to roll out a similar approach for handling customer service in the works.

Boosting productivity by automating repetitive tasks with generative AI

All those companies who have introduced generative AI understand one thing: it is a solution which serves to alleviate the workload of employees, allowing them to be more productive and efficient without spending hours and hours on tasks that can be easily automated.

These kinds of tasks are usually repetitive and time-consuming, not requiring any special knowledge or creativity to be carried out satisfactorily, and often causing a good deal of frustration or boredom amongst employees.

Currently, Narrativa has the technology to provide these types of natural language solutions to companies: from personalized financial insights or the generation of news articles to solutions for the health sector, particularly pharmaceutical companies that have huge amounts of data to process.