How AI used to Optimize Personalization with The Help of Data-Driven Platforms

How AI used to Optimize Personalization with The Help of Data-Driven Platforms

Artificial intelligence has triggered an unstoppable process.

In our globalized world, those who take advantage of the use of Artificial Intelligence Programming will acquire a leading position in the market: they will be able to anticipate their needs, attend to them and be able, even, to generate trends and needs in their target audience.

Artificial intelligence is one of the fundamental drivers of the technology sector, with a growing level of importance in all types of scenarios. From a purely personal point of view, mid-range Smartphone already includes features such as face recognition, speech to text, cognitive services -Siri and Cortana- or receive information from a recommendation system to plan a vacation day. AI Programming Software is leaving its mark in a number of areas. Some of the most important are those that will be discussed below.

1) Virtual Assistants

The objective is to recognize, through language, the needs of the interlocutor and to model an adequate response using a language that is close to them. The current approach is to have a central module (dispatcher) capable of understanding the main motivation of the speaker to refer to specialized bots in each of the areas.

This is implemented with Mobile App Development Services for the topmost solution of run interms of accuracy. These assistants are complemented by modules that perform voice recognition in practically any context, they can personalize the response with different voices, they have an almost human appearance and the answers are selected according to the speaker and parameters such as their diction, their emotional state or its geographical location.

2) Smart Devices

The miniaturization of the basic components and the cheapening of communications provided the first wave of sensors able to partially recognize their environment and send information to a centralized system from where, for example, issue alarms based on the data and context. Even at this level, the devices were able to adapt -with simple rules- some behavior that did not require the participation of a person. The Android Application Development Company is trying to adopt the complex nature of devices to perform intelligence processing.

3) Decision making

The classic decision support Artificial Intelligence Programming has focused on the strategic needs of mobile app Development, leaving the operational in a mere reporting. Indicators and reports describe the current situation (descriptive intelligence) and extrapolate trends with a view to the future, trying to anticipate changes. The application of machine learning was very restricted to certain areas (banking and insurance). This vision -relevant in strategic decision making- has been overtaken by the variety and amount of information that is required for operational data collection in a new, more dynamic context.

4) Smart processes

The point of great impact in the near future will be the incorporation of IA pieces in the process flow of an organization. This orientation has been one of the most successful models, thanks to advantages such as the independence of processes with respect to people, the creation of effective value chains or departmental specialization.

But its level of growth has generated bottlenecks, increased by the need to work with an increasing number of data and flows. The AI Programming Software works on automation of processes from rule engines and robotization has allowed alleviating this burden, but the use of AI is called to revolutionize the very essence of business processes.

Read the blog- What is the latest in Artificial Intelligence

Initiatives have already been developed that capture a flow of processes, understand information, filter it and prioritize it to take it to a human decision maker. These initiatives use AI in many ways. They extract relevant information from documents applying cognitive technologies to present only the relevant and follow the flow of processes with the least relevant elements.

These initiatives are found in law firms or in the public sector to reduce the internal bureaucratic burden for Mobile App Development Services. They apply risk patterns to the entry of information, which allows the bank to detect possible fraud in real time or, in the case of direct sales, analyze the risk of an operation or the abandonment of a client in a CRM.


These functionalities are now included as parts of a BPM, just like any other element. AI algorithms are created, published and integrated with their own life cycle; and, unlike the rest, they can self-evaluate and change their behavior autonomously. It works on the Android Application Development Company for the best possible implementation.

This is the first step. In the future, the processes themselves will be defined by expert systems and will change to adapt to the environment in which they are developed. Some lukewarm initiatives in the framework of industry 4.0 have begun to address - in a supervised way - the productive processes in the plant, proposing to the responsible (human) the changes that have to be made in a system that feeds on this experience. Contact for best results.