Maybe; Sometimes, we face barriers when assimilating new technologies in our companies, this article aims to help those who see the issue of Artificial Intelligence as something complicated to achieve, as science fiction, as something complex in the implementation for your company or as something that I know I have to do. Still, right now, I do not have the time.

Based on our company’s own experience, removing all the layers of complexity, and without entering a more specific technical speech, I will summarize you very concrete examples of use that confirm the theory that the Artificial Intelligence is the new electricity.

You will see how in each of the examples, AI is like a hidden liquid flow that is already working behind the different systems and areas of our company.

As time goes by, these AI micro applications that nowadays solve small specific problems will start to grow, relate, and evolve until reaching practically any corner of your company.

If you are one of those who think that AI will replace you in a short period, you will find reasons in this article; if, on the contrary, you believe that AI will amplify your capabilities, you will also find reasons in this article.

Below I list the areas of activity in which we are already working with specific purpose AI:

1. Invoicing – Preventive security.

This does not come in any business plan of your company. It is still the Achilles’ heel of the new generation startups that we bring to the market, whether it is an eCommerce, a SaaS, or a Multilateral Platform.

The problem is called “delinquent churn,” and it’s the criminal actions that users carry out in the economic transaction with your platform, such as card theft, identity theft, cloned cards, etc. There are more than 200 different reasons why a payment can fail, and the failure rate is alarming.

The vast majority of us use Stripe as a payment gateway; this American platform has implemented automatic fraud detection systems, which are based on automated learning processes that compare and train data on a large scale of all its customers.

They thus provide a real-time transaction risk score at the time of payment, predicting whether that user or card comes from a fraudulent source before payment is made.

2. Management – KPIs in predictive mode

As we have mentioned, regardless of the type of activity that your company carries out or the platform or operation model, we all have our KPIs or metrics. In my case, it is a “SaaS (Software as a Service)” platform with monthly or annual subscription payments.

Surfing, we discovered ProfitWell’s platform, as experts in calculating metrics for subscription businesses, this technology does not stop adding all your data and offers you in a very schematic and analytical way which is the state of the number of users, the liquid entered, the new trials, etc.

The idea is that they have a predictive model at the beginning of each month that tells you what you are going to invoice at the end of that period of the month, or what your growth rate is going to be, or how many new users you are going to have one month in advance.

After several months of use, I have to tell you that the predictive AI model works very well. In a way, a month in advance allows you to anticipate your business’s behavior at all levels.

3. Marketing – Generative audio.

As I told you in the article “The 3rd Disruptive Generation, is already Generative” when editing the narrative voices of marketing videos, we use an application called “Wellsaid”, in which you access a huge bank of processed digital voices that simulate different tones, genres and uses.

As a button shows, here is one of the videos in which you will find it very difficult to identify whether the narrator’s voice is human or artificial.

4. Customer service – Chatbots.

We are working on the development of a bot that will support users on the website, any technological platform that requires certain actions by the user, is a process in which the customer has many questions at each stage of the funnel, the bot simply resolves that first communication action to resolve that question quickly.

I admit that I had my doubts with the bots since I do not see it at all the user’s adaptation to directly establish a conversation or communication with a machine. But after analyzing it in detail, we will launch our bot next year.

5. Product roadmap.

Data relations.

Our product’s main core is not found in the data itself, but we offer about companies, markets, and business patterns in the data’s relationship.

We went through a manual and human learning process to see how to make these relationships, serving as a basis for a later phase of AI implementation that is educated to make the connections between the data by itself according to the learning done.

Canvas analysis.

The most important task within the company and the one that brings more value, lies in the analysis of the business model canvas of companies around the world, in the medium term we are preparing an AI that reads the information on the Internet, extract the parts of the text of the analysis, and classify the text within its categories of the business model canvas.

This development raises the company’s levels of scalability to another level since this particular application means a considerable cost reduction in the hours of human analysis.

Generative Business Model Canvas.

And the cherry on top will come in the future with the design of a generative business model, in which the user will introduce four input words that define the company he wants to design.

On the way out, he will get a business model created by the combination of data that an autonomous Artificial Intelligence will perform.

As an example below, I show a business model that has been created from the entry of 4 words, “entertainment,” “advertising,” “community,” and “micro-payments” within five years, we will automatically create business models like the one below.

Conclusions.

Yes, I admit it, AI has seeped into all the arteries of the startup, and I have the feeling that as time goes by, more and more areas of knowledge of our company will be added, creating a base or structure in which all areas of activity communicate under the same imperceptible flow of AI.

After a simple way I have just demonstrated in this article, today the access to this technology is available to everyone. We are moving from the early adaptation phase to the phase of widespread implementation.

This shows that in a brief period of the last five years, a very exponential jump is being made, confirming the theories of the significant impact that AI shortly will have on our lives.