Artificial intelligence is an integral tool that enables digital transformation by integration of data, analysis and real-time insights for better decision making. AI engineering focuses on developing tools, processes, and systems to enable the application of AI in real-world contexts. AI is being used widely across a variety of sectors, such as manufacturing, finance, retail, healthcare, transportation, and construction to name few. It addresses issues in development of products or services and offers recommendations to get the most out of AI while protecting important human values.
According to a project undertaken by PriceWaterhouseCoopers, “Artificial Intelligence technologies could increase global GDP by $15.7 trillion, a full 14%, by 2030.” Due to the pandemic, there has been an increase in digital transformation across a variety of industries, much faster than expected. This has resulted in a focus shift towards AI-enabled transformation which solves significant business problems with business-focused solutions.
It is interesting to see the business landscape that is changing with AI for the better. Some of the few critical trends of 2022 include:
AI for Security & Surveillance –
Face recognition and voice recognition combined with video analysis, assists in video surveillance and security systems to identify abnormal behavior patterns.
AI in real-time video processing –
A pre-trained neural network model, a cloud infrastructure, and a software assist in modern real-time stream processing for applications such as background removal and blur.
Conversational AI chatbot –
Contextual AI bots use Natural Language Processing (NLP) to understand text and voice provided by users, whereas Cognitive bots learn from old data to understand root cause to provide real-time assistance.
AI-driven QA –
Computer vision and deep learning systems are used for AI inspection to analyse, identify and detect defects of products in assembly lines and equipment monitoring.
AI in IoMT –
AI powered camera combined with analytics to analyze potential threats and make accurate predictions, helps in reducing preventable medical errors through surgical platforms.
Low-code or No-code AI – Shortage of skilled AI engineers may hinder the enterprise-grade application development, but low code platforms address this issue by providing intuitive interfaces that can be used to create complex systems.
Deployment of AI in business helps in reaping tangible benefits, including material gains. Some of the important benefits AI brings to businesses are efficiency and productivity gains as AI technology handles tasks at a faster pace. AI enables shorter development cycles, ultimately improving the speed of business. It opens up wide range of capabilities and business model expansion. A strong AI engineering strategy is important to build better customer experience, improved real-time monitoring, better quality, error reduction, and streamlined processes.
AI is a transformative technology that replicates human functions such as planning, problem-solving and reasoning. If you think your organization also needs a strong AI engineering strategy, leverage Innominds’ AI, ML, Data and Analytics Engineering services to get relevant insights from your data in real time and create great customer experiences with our data and AI/ML engineering expertise. To harness the power of AI-driven data and analytics engineering, Contact Us.