Digital Transformation & Artificial Intelligence (AI) are critical drivers for several industries which will enable companies to deliver value to their customers in a highly competitive and ever-changing business environment.

The digital technologies like AI will help companies become more innovative, more flexible, and more adaptive than ever. The digital transformation journey leads companies to create or modify customer experiences and culture, and business processes, thus meeting customers’ changing needs and the market.

AI drives digital transformation with promise of speed, ease, and cost optimization, while simplifying complex processes and systems.

AI is already here, being used by many companies looking to optimize their business. Let’s see how Artificial Intelligence can help your business as one of the most potent enablers of what we call Digital Transformation. But what is Digital Transformation?

Defining the Digital Transformation

Digital transformation is a set of processes, methodologies, and tools used by modern companies to optimize their operational activities, such as providing differentiated service, increasing performance, and increasing its reach power, with employees and customers as a priority.

However, digital transformation is not just a new department in the organization, but it is a game-changer in technology’s role in the corporate environment. That’s why it is currently being considered as the 4th Industrial Revolution.

But more than a concept, digital transformation has become a movement that attracts companies interested in reviewing processes, innovating, and gaining competitiveness with the help of technology.

In the context of transformation, technology is not an end, but it is a set of tools that need to be at the service of the company’s business strategy.

And today, no matter in what industry your business is operating, with a considerable probability, your business use technology to deliver products or services.

With a very similar probability, your competitor is technology-based too, and they can come from any segment.

But on the other side, there is still a lot of technology investment to be done, and the impact hasn’t even started.

Data and Artificial Intelligence (AI) are critical factors in the strategy for those who want to expand their business impact in this digital transformation journey. Data only makes sense if it is aligned with the process and seen as the company’s competitive advantage.

Do you speak data today?

Getting value from data is at the heart of any digital business transformation.

The enormous volume of data, coming from different sources and formats, such as structured (ERP, Database, etc.) and unstructured (social media) data, if treated correctly, can help your business to understand better the desires of your customers, the market where they operate and your competitors, bringing insights for increasingly intelligent and agile decision making.

The use of data is a central point in the management of companies in their digital transformation. It is essential to have a strategy to use them as a means of having a competitive advantage.

For example, using more advanced analysis, based on qualified data, to beat the competition.

Building an efficient and comprehensive Data Literacy is the only way to be effective on a real scale and bring insights to the business in a collective effort to make sense of all that information.

It is necessary to establish processes and resources capable of connecting, structuring, and analyzing this data.

Companies understand the value of investments in innovative technologies and processes capable of analyzing data more efficiently and quickly — allowing them to reap these investments’ benefits.

AI drives Digital Transformation

With the possibility of integrating different systems and automating several daily tasks, the digital transformation took another leap when Artificial Intelligence (AI) and Machine Learning (ML) became part of many organizations’ business strategies.

In addition to resulting in faster and more efficient operations and, therefore, more productivity, these technologies are so important in the digital transformation because they allow better use of the data collected by your company in several ways.

In a reality in which 90% of all data produced in history has been generated in the past two years, it is necessary to make sense of them. As the famous saying goes, “data is the new oil.”

Machine Learning and AI allow us to use all this amount of information to take the company further, either by improving current products and services or by the possibility of new innovative strategies.

Undoubtedly the most significant impact is the learning that the machines gave to the human being, a much more excellent notion about the scenario that we are inserted in.

Artificial Intelligence (AI) and Machine Learning (ML) are two of the most potent protagonists of digital transformation, and the basis for the most efficient digital tools developed today. They are enablers of increasingly innovative and effective solutions that directly impact the market’s acceleration and competitiveness and customers’ experience and expectations.

How to start Digital Transformation?

A persistent question that may come to your mind regarding data is what you should do with it and where you should start.

I will try to add my two cents to help you answer those, but also, you may be in the condition to ask other common questions like:

· How can data improve my customers’ experience?

· Should I hire someone?

· Should I invest in a database?

· How do I know I have enough data to generate intelligence?

I should say that the first job to be done, which is also a challenge, is to gather all your data in an organized way and start processing it so that it becomes strategic information for your team or company.

From experience, I believe that there is no lack of data. But it is true the opposite — the contrary. “There are many sources of internal and external data, but everything is spread out, different platforms, databases, silos, paper piles, everything is loose across your company. You need to find it and organize it.

Your journey to Artificial Intelligence

Following the path opened by digital transformation, there is no way to have artificial intelligence without having a clear and defined data strategy.

There is no point in seriously talking about Artificial Intelligence if you do not have your data organized.

It would be best if you did your homework before starting experiments with AI and Machine Learning.

Start importing the data and storing it efficiently, preferably on the cloud. Today is becoming more challenging to keep the crescent amount of data produced by any business organized sustainably on a server or in a data center. Cloud is the direction you will probably want to follow.

Investing in Artificial Intelligence is to train the machine and the algorithms from databases that are organized for that to happen. To help this task, an ever-growing computational power is available on the cloud to solve anything.

The following is a proposal of the necessary steps to reach the stage of maturity in the use of AI to optimize its production process with all the potential available effectively, based on the SingleStore Maturity framework:

1. Collect data: first of all, it is necessary to have data; AI is hugely dependent on data, examples, and instruments that serve as samples for training models that assist in decision making. This data can be extracted from databases, spreadsheets, markup files such as XML, etc.

2. Storage: in addition to collecting data from safe and quality sources, it is necessary to use tools for storage, structuring, and integration that facilitate data exploration analysis. Here are ETL-type tools (Extract, Transform, and Load) responsible for extracting, transforming, and even loading data. Such devices are essential to prepare the data for the next stage of exploration.

3. Exploration: in this step, descriptive analyzes are made. BI (Business Intelligence) reports, datamart tools, OLAP queries (Online Analytical Processing), and analysis panels are built from the data collected and stored so that specialists can have a clearer, more compact, and objective view of sectors and the operation of the organization as a whole.

4. Real-time operation and extraction: this is a level of maturity at which the organization is concerned with integrating its data with modern tools, many of them on servers in the cloud, using APIs (Application Programming Interface, the transformation of data in formats of easier integration like JSON (JavaScript Object Notation) or XML. Such strategies facilitate integration in real-time and improve the response time from creating data to more improved analysis.

5. Prediction and Optimization: at this stage of maturity, the organization already has quality data, in real-time, in formats compatible with the leading technologies used for training machine learning models and is capable of making decisions based on analysis and prediction. High-level algorithms are developed at this level, capable of recognizing voice, images, recommending, learning from patterns, etc.

Digitization value through Artificial Intelligence?

Just as the advent of the internet has changed the way the world has always done business, emerging technologies, especially artificial intelligence, are gradually entering the daily lives of businesses worldwide.

The question is no longer when the digital transformation will arrive in all small and medium-sized companies, but what technologies will be essential and prioritized.

Artificial intelligence can be used in corporations in various industries. The following examples can serve as a basis for technology companies’ leaders to better understand opportunities to provide SME services.

To create value with a product, digital transformation must be applied, with artificial intelligence identifying information to help the involved professionals in various stages of a process, such as design, execution, and delivery.

With everything digitalized, you may start checking the phases that need adjustments in the project; for example, in the design phase, AI improves research, development and makes an accurate forecast of the next steps.

In the execution phase, continuous maintenance is the critical point where AI and Machine Learning can help. These are responses in real-time to what is being researched.

When delivering a product, it is, as previously mentioned, the customer experience that you will provide with everything digital, AI, and Machine Learning can be used to monitor, recommend and forecast actions to reinforce your product, brand, and market share.

Why is early adoption important?

McKinsey estimates AI techniques can create between $3.5T and $5.8T in value annually across nine business functions in 19 industries, generating up to $2.6T additional value in Marketing and Sales and up to $2T in Supply Chain Management and Manufacturing.

Also, AI will add $200B in value to Pricing & Promotion and $100B to Customer Service Management in Retail.

McKinsey predicts AI will have an 11.6% impact on Travel industry revenues and up to 10.2% on High Tech.

And in most of these use cases, AI and deep neural networks improved performance beyond what existing analytic techniques were able to deliver.

As you can see, there are several reasons for you and your business to bet quickly on Artificial Intelligence technologies, and I like to focus on three of the most relevant:

1. The necessity to monitor and combat legacy’s “technological DNA,” which guarantees agility to innovate and deliver services quickly;

2. The necessity to offer products and services increasingly directed to the individual needs of customers, in an omnipresent and assertive manner;

3. The potential to multiply the business value through automated processes and offers increases the efficiency of operations.

It is also important to mention that, by strengthening these operational capacities with Artificial Intelligence, your business will also enhance its resilience to global crisis scenarios by offering products and services with increased profitability and creating predictive capabilities for their business.

Artificial Intelligence means to the digital transformation what electricity has meant to humanity in the past.

Its disruptive power is so great that we move towards a stage in the economy where digital products will be increasingly intelligent to make recommendations, present options, and help customers make their choices.

The biggest challenge for all of us is to manage all these changes and deal with such a transformation in the organizational structure.

Investing and developing skills among the entire workforce to adapt to new models and trends is critical to bring positive results.