How to apply artificial intelligence in your company

The application of artificial intelligence (AI) in enterprises can help improve productivity, performance and growth. Many organizations are aware of this but are faced with the problem of not really knowing where to start applying AI.

There are many companies facing this challenge, and while each has its own organization, needs, training and vision for AI, the first thing that is needed is to understand what artificial intelligence can do and how they can leverage it.

That is why we have created this article, to serve as a basic guide for those organizations that want to introduce AI and are not sure how to get started.

Differences between predictive and generative artificial intelligence.

First of all, we consider that it is important to understand these two main branches of AI, because although they share a technological base, their application and use cases are very different and therefore should be treated separately:

Among their main differences stand out:

• Their objective: generative AI focuses on content creation, while predictive AI is dedicated to anticipating future results based on historical data.
• Their application: predictive AI is especially interesting for decision making with more and better information of what may happen in the future, while generative AIs have a more important place in creative fields such as text generation, art or design.

Predictive artificial intelligence: what it is and what benefits it offers.

Let’s start by talking about predictive AI and how to apply it in enterprises.

This branch of AI focuses on predicting future outcomes based on historical data. Thanks to the use of advanced algorithms, it is capable of analyzing large amounts of data to identify trends, relationships and correlations that are imperceptible using other conventional analysis methods.

Among the main benefits that this artificial intelligence offers to companies we can highlight:

• Improves decision-making: as it provides crucial information, making it possible for management teams to anticipate changes in the market to minimize risks and better capitalize on opportunities.
• Optimizes processes: as it can identify areas for improvement to reduce operating costs and increase operational efficiency.
• Improves customer satisfaction by facilitating the customization of products or services by anticipating customer needs, behavior and preferences.
• Delivers sustainable competitive improvement by making companies more agile, adaptable and data-driven than their competitors.

How to introduce predictive AI in your company from scratch.

As we have said, each organization has a different nature and needs. This can affect the process of implementing artificial intelligence, although in a generic way we could define the following steps to follow.

Assessment of needs and objectives.

A predictive AI is in charge of foreseeing tomorrow to improve decision making today. Therefore, the first step to take is to identify where it has a place in your organization.

In other words, you need to identify what decisions are being made to see where AI could offer an improvement. This requires an inventory of both strategic and operational decisions to better understand where it can add value.

Data preparation and collection.

This type of AI relies on analyzing past data to make predictions, so an important part of the process is to collect and prepare relevant and high-quality data for use in developing predictive models.

Explain that sometimes the data needed to develop an AI project is not available at first, but when you are clear about the use case you can evaluate how to get the data you need and put in place the necessary mechanisms to start collecting that data.

It is advisable to start by selecting a project of an adequate size so that it can be developed in terms of resources but can show significant results, as a pilot action within the organization.

Predictive model building and training.

In this phase, predictive models are developed using algorithms appropriate for the company and its data sets, and validated before implementation.

In addition, a platform must be selected that offers ease of use, scalability, ability to integrate with other company assets, etc.

Implementation and monitoring.

Once the predictive model has been validated, it is implemented within the actual business process and monitored to evaluate its performance and make any necessary adjustments.

After completing this first AI implementation experience and based on the lessons learned, it is possible to consider extending its use to other areas of the company. The important thing here is to expand its use progressively and carefully, involving all relevant teams and ensuring alignment with the company’s strategic objectives.

Examples of predictive AI applications in companies.

The applications of this technology in the business world offer many possibilities. As we will see below, its application can be made at all levels within a company (from more strategic to more “everyday” decisions) and for organizations of all types of sectors and sizes.

For example, applications such as Netflix or Spotify use predictive AI for suggestions to their users to achieve more playing time and greater satisfaction. Amazon does something similar when making product recommendations, taking into account your purchase history, browsing patterns, user behavior, etc.

Tesla incorporates predictive AI in its self-driving vehicles, which analyze their environment in real time and predict traffic and pedestrian behavior.

Coca Cola uses this type of AI to optimize inventory management and distribution using demand prediction models, which allows them to minimize storage costs and maximize product availability.

If we talk about more uses in organizations of other sizes, we could mention these examples:

• Predicting customer behavior in retail: allowing for increased personalization of offers and predicting the impact of different marketing actions both online and offline.
• Disease detection in healthcare: AI has the ability to detect and correlate signals that can lead to a premature diagnosis that otherwise could not be made.
• Candidate selection in human resources: thanks to the optimization of the process of reviewing profiles and resumes, something that usually requires a lot of time from selection teams.
• Detection of financial fraud: the analysis of fraud patterns and real-time data processing make it possible both to detect cases as they occur and to help prevent them.
• Optimization of maintenance in industry: automated production lines are equipped with numerous sensors that collect data of all kinds. The processing of both historical and real-time data makes it possible to detect anomalies that anticipate the appearance of wear, defects or problems.

Generative artificial intelligence: what it is and what benefits it offers.

Let’s talk now about Generative AI and how to apply it in companies.

Although the underlying technology is the same as in predictive AI (neural networks), its applications are radically different. It is important to understand well the capabilities of Generative AI, because it is on the basis of these that we can define well the uses we can make of it. 

So what is Generative AI particularly useful for?

As its name suggests, to generate content. This type of AIs, based on millions of texts, images and videos with which they have been trained, are able to create new texts, images and videos from scratch without human intervention, beyond a small description of what you want.

But in addition to this content generation, Generative AI has other characteristics that make it especially interesting for companies.

Characteristics of Generative AI.

The first of these is the ability to understand the meaning of text. It is not only about generating text, but with this technology you can extract its meaning in a very precise way, in order to be able to make decisions or take actions based on the understanding of this meaning.

In addition, Generative AI and in particular LLMs (Large Language Models) can be used as small reasoning machines. 

Combining the ability to understand text with the ability to generate responses results in a technology capable of providing reasoned answers, something that has great potential for very interesting applications.

Based on the above, Generative AI has two main areas of application in the enterprise.

On the one hand, there are a multitude of user tools that manage to increase the productivity of each person individually, such as ChatGPT or similar.

On the other hand, in addition to these user or office tools, Generative AI can be applied to solve complex business problems. Some examples would be:

• SentimentAnalytics: this is one of the applications of LLMs, which can understand and generate human language in an advanced way. Sentiment Analysis (or sentiment analysis) allows processing language to identify and extract subjective information from resources, something with great potential in applications such as survey analysis, monitoring of comments on social networks, evaluation of customer service responses, analysis of product reviews, etc.
• Integration with Natural Language (ILN): also within LLMs, it allows to improve customer service with more efficient and faster conversational interfaces (such as chatbots), thus allowing to reduce service times, and to offload the human team so that they can dedicate themselves to more valuable tasks.
• Content generation: as we have already mentioned, we are talking about creating texts, images, videos, music, etc. in an autonomous way, helping companies to maintain a more active and visible communication in a simple way.

How to get started with Generative AI in your company.

As with predictive AI, each organization must evaluate its own nature and needs to see how it can use this technology. In any case, when introducing Generative AI in your company, we recommend you take these steps into account:

Train teams in the use of Generative AI.

According to a Salesforce report, 39% of Spanish people believe that mastering Generative AI will provide them with some improvement in their work. Similarly, the report also warns that the lack of clearly defined policies around its use “may be putting companies at risk”.

The study was carried out in 14 countries. In the Spanish case, 84% of workers believe that their company does not have defined policies on the use of Generative AI at work. If you add to this that a high percentage have not received specific training on its use, the result is that many teams and workers will be using this technology in an inadequate way.

Generative AI can also act as a talent magnet. Many workers report being attracted to companies that use it on a regular basis, and believe they would feel more engaged with their employers.

Therefore, an important step for companies wishing to incorporate AI is to define an application framework that is safe, ethical and reliable, train workers and break down barriers so that they can use it effectively.

Identify the application areas where Generative AI can be most effective.

We are talking about a very flexible technology that is evolving almost day by day, so its possibilities within a company are very numerous. Let’s take a look at some examples where Generative AI has great potential within the business environment.

• Customer behavior analysis.

One of the most interesting possibilities of Generative AI is the hyper-personalization it enables.

Although today consumer product distribution companies are not yet able to provide each individual customer with personalized content, this is achievable with this technology.

For the time being, it is already possible to analyze customer reviews of a product or service, their opinions in surveys or their posts on networks, to find out what they think and how they feel.

• Interaction with users and customer service.

Generative AI works as a true virtual customer assistant.

An AI-based chatbot can attend 24/7, offering recommendations proactively and making complex customer problem resolutions simpler and faster.

Initial mistrust aside, it is a fact that AI and customer interaction has been growing and is now accepted as an everyday occurrence, although it should not be forgotten that balancing technology with human presence is still essential to create positive experiences for users.

• Creation of chatbots with expert knowledge of your company.

Generative AI allows the creation of chatbots fed with databases and specific knowledge sources of companies, which makes them excellent assistants for the resolution of doubts or questions in different areas of the business. 

Some examples could be chatbots for resolving customer queries, or chatbots to contain information on the operation of the machinery of the entire company, among other possibilities.

• Creative content generation.

This technology is a powerful tool that drives not only efficiency and productivity, but also innovation and creativity.

Generative AI systems are capable of creating original designs or producing texts and music, to give some common examples.

Corporate communication managers can take advantage of these possibilities to explore new ideas and forms of expression, being able to produce content more efficiently, saving time in the creation process, adapting each piece quickly to different audiences, and all while maintaining a linear idea in tone and style.

 

We help you move towards a future driven by artificial intelligence.

Adapting artificial intelligence prepares companies to adapt to a future where technological innovation will play an increasingly important role. Those companies that take advantage of this opportunity will be better prepared to succeed in a competitive and constantly evolving marketplace.

The path to successful implementation of artificial intelligence requires commitment, an innovative mindset and collaboration with partners that will foster success. If your organization is in this process and you are looking for a partner with experience in both the initial analysis and execution of artificial intelligence projects, do not hesitate to contact us.