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Top 10 Artificial Intelligence (AI) App Development Trends

Artificial Intelligence (AI) powered apps help business in predicting customer behaviors, smart decision making, and others, which are the most critical factors to increase sales and earn hefty profits.

Published

5 years ago

September 16, 2019

TwinzTech

10 Artificial Intelligence App Development Trends

Several technologies have impacted mobile app development to a greater extent – Artificial Intelligence (AI) is one of those. App developers today leverage AI technology to build more advanced, intelligent, and smart apps to cater to multiple industries.

AI-powered apps help businesses in predicting customer behaviors, smart decision-making, and others, which are the most critical factors in increasing sales and earning hefty profits.

It has increased the demand for AI apps and thus encouraged developers to adopt the latest practices and trends to make apps more advanced. Let’s discuss here some popular artificial intelligence app development trends.

Table of Contents

1. Personalization

There are many factors responsible for the massive expansion of artificial intelligence and machine learning (ML) – analyzing and predicting user behavior is one of them. And it helps business caters to customers’ personalized recommendations. This is the reason why Artificial Intelligence (AI) and Machine learning (ML) witnessed their fast adoption in multiple industries, apart from gaming.

Mobile application development agencies nowadays build AI-powered apps incorporated with business strategies, which offer personalization on a larger scale. The app personalizes user interaction and thus helps the business personalize the customer experience.

Artificial Intelligence App Development Trends

2. AI is Getting Closer to IoT, Blockchain, and Cloud

The year 2019 already witnessed the combination of artificial intelligence with various other technologies such as the Blockchain, Internet of Things (IoT), and Cloud for mobile app development.

Meanwhile, these technologies are individually used for mobile app development as well and are famous for their attributes. For instance, IoT can predict customer behavior; Cloud offers vast storage space, and Blockchain technology is highly secure and maintains transparency.

Need not to mention; apps developed on these combined technologies will be more robust, advanced, and feature-rich.

3. AI Shares Space with Data Analytics

Getting a complete insight from data analytics and understanding it is a time-taking process. They witnessed the combination of artificial intelligence with data analytics. It helps businesses in getting smart data insight most naturally.

AI-based algorithms are highly efficient in generating insight from multiple channels and help businesses in gathering smart data. In other words, it makes the task of gathering insight, convenient, and less time-consuming.

Apart from this, it empowers business growth by improving decision-making efficiency, capability, and lots more.

AI Shares Space with Data Analytics

4. NLP Gets Boost with Speech Recognition

Natural Language Processing (NLP) enables a computer program to communicate with humans. As a popular component of AI, NLP helps computer program quickly perceives human language.

It works on two essential factors, including syntax, which makes any sentences meaningful by arranging words, and semantics, which defines the meaning of words.

Be it sarcasm, emotion, or other things, NLP algorithms are capable of decoding everything. Besides, data extracted by voice assistants from speech can be combined perfectly with deep learning to gather the real meaning of the words expressed with emotions.

5. Explainable AI

Explainable AI is based on the concept of the black box in ML. It focuses on how black-box decisions in artificial intelligence are made. It discovers and understands several steps involved in making such decisions.

As discussed, AI improved the efficiency of the business in decision-making. So, explainable AI has a significant role in this arena. With this, business executives will be able to get the exact reasons behind certain recommendations that are made.

The credit goes to explainable AI for making the entire process of decision-making transparent and making decisions unbiased completely.

6. Facial Recognition

Facial Recognition

Facial recognition is another fast-growing technology that can easily recognize an individual from a digital image or video frame. Despite having specific challenges such as illumination, expression, etc., face recognition is considered to be the essential feature of AI-powered apps. Its demand is growing day by day. This prompts app developers to include face recognition to create resonating AI apps.

7. Quantum Computing

As the name suggests, quantum computing is involved in using quantum-mechanical phenomena including superposition and entanglement, for performing the computation.

Quantum computing is playing a vital role in enhancing the task of artificial intelligence and thus helps researchers and developers in solving near-term issues. The credit goes to Google AI Quantum for making quantum computing highly advanced by creating novel quantum algorithms and quantum processors.

8. Safety and Privacy

Safety and privacy are the most important things, which are always taken into consideration for AI app development. In the year, protection and confidentiality emerged as the hottest AI app development trends. App developers consider all critical security aspects of protecting apps from potential threats and building highly secured AI-powered mobile applications.

9. Neural Networks

Neural Networks

Also called artificial neural networks, neural networks work similarly to human brains. It can store essential data in a digital format and uses the data for classifying the information. Neural networks witnessed a growing demand in different fields that include stock market prediction, music composition, diagnosing health issues, etc.

Neural networks witnessed a growing demand for AI app development. The integration of neural networks makes AI apps more sophisticated and purposeful.

10. Deep Learning

Deep learning is called an essential subset of artificial intelligence, which can imitate the human brain when it comes to data processing and creating patterns used for decision-making.

Deep learning got more attention from app developers, who leverage this technology in AI app development more frequently to improve the app’s usability with features like automatic text generation and others.

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AI Tools

A Guide To Using AI for Knowledge Management

Using AI for knowledge management and to transform massive data pools into actionable insights is not just beneficial; it’s becoming a necessity to stay competitive.

Published

2 months ago

May 22, 2024

TwinzTech

In the digital era, the fusion of AI technology with knowledge management is revolutionizing the way organizations manage and exploit their informational assets. Using AI for knowledge management and to transform massive data pools into actionable insights is not just beneficial; it’s becoming a necessity to stay competitive. Keep reading to unlock the full potential of AI-driven knowledge management.

1. The Intersection of AI and Knowledge Management: A Synergy Explained

Knowledge management traditionally involves capturing, organizing, and distributing knowledge across an organization. When AI steps into this territory, the potential for enhanced efficiency and decision-making emerges. AI algorithms can sort through and analyze data at a rate no human can match, revealing patterns and insights that can be critical for strategic planning. This melding of AI with knowledge management practices is a modern alchemy, creating an invaluable resource.

One of the most significant benefits of integrating AI into knowledge management is the automation of data processing. AI systems can continuously learn from new data, refining their algorithms and providing even richer insights over time. Moving from static data repositories to dynamic knowledge hubs, businesses are now armed with constantly evolving intelligence. This represents a profound shift from data being a static historical record to a dynamic, predictive tool for decision-making.

Using AI for Knowledge Management is a top solution

Customization is another strong suit of AI in this space. Rather than one-size-fits-all information resources, AI can personalize knowledge dissemination to the needs of each employee. The focus moves beyond mere information access to ensuring the right knowledge reaches the right person at the right time.

2. Implementing AI in Your Knowledge Management Strategy

Transitioning to an AI-driven knowledge management system begins with identifying the scope and objectives of knowledge needed. Organizations must be clear about the kind of knowledge that is most valuable and how AI can aid in its cultivation and dissemination.

Following initial evaluations, the selection of appropriate AI tools and technologies becomes the next crucial step. There are various AI solutions designed for specific knowledge management tasks, from natural language processing for content analysis to machine learning models that predict trends and behaviors.

Integrating AI requires a cultural shift within the organization. Employee buy-in is crucial, and it is important to address any concerns about job displacement head-on. Training and educating the workforce on the benefits and use of AI systems can facilitate smoother adoption, ensuring everyone understands the role of AI as a partner, not a replacement, in the knowledge ecosystem.

3. The Impact of AI on Knowledge Retention and Dissemination

An AI chip sits in a computer

The true value of AI in knowledge management is often most visible when assessing knowledge retention and dissemination within the organization. AI-driven systems can significantly enhance the ability to capture institutional knowledge, store it and make it available in engaging, interactive formats that increase retention.

Analytics are also central to measuring the impact of AI on knowledge management. By evaluating these metrics, businesses can see whether the knowledge is being leveraged effectively, which areas may need more focus, and where improvements can be made.

Furthermore, AI can be a boon for training and development programs. By adapting to the learning pace and style of individual employees, AI can deliver personalized training recommendations and content, leading to more effective learning outcomes.

Altogether, AI is transforming the realm of knowledge management with its capacity to automate, personalize, and revolutionize how information is processed and utilized. Challenges notwithstanding, the rewards of integrating AI into knowledge management strategies are profound, paving the way for smarter.