The world of data science and machine learning moves fast—faster than most people realize, actually. A key challenge that enterprises face is keeping up with the myriad innovations happening in the field so they can stay ahead of their competitors and customers. In this article, we’ll explore five trends we predict will shape machine learning in 2022.
1. Blockchain Meets Machine Learning
Blockchain technology is going to revolutionize every industry it touches, especially as it continues to evolve. The rise of cryptocurrency is indicative of how blockchain has already started re-shaping our economy; however, its effect is going to grow exponentially in coming years. By 2030, blockchain technology will have started an economic singularity (and it won’t be pretty). You can hire blockchain developers at a low cost and embrace this technology.
2. AI-Based Self-Service Tools: Autonomous Business
Many of today’s workforce is already familiar with self-service technology, which saves businesses on overhead. This trend will only continue to grow, both in popularity and sophistication. At a basic level, AI-based self-service tools can make it easier to handle routine tasks; at a more advanced level, they can address many customer queries themselves and proactively send notifications to staff when an issue arises.
3. AI Assistants: Getting Personalized Help From Bots
Personal AI assistants are an emerging trend that will continue to take hold in tomorrow’s workplaces. At present, their capabilities remain limited, but these digital helpers will soon be able to do much more—helping us improve productivity and tackle our ever-growing workloads. Watch out: Businesses must tread carefully as they introduce AIs into daily work life.
4. Personal Medical Devices: Accessing Complete Healthcare Data
Personal medical devices promise to revolutionize healthcare. As big data analytics and machine learning technologies mature, we’ll begin to see more and more patients bringing their own medical records with them. From wearable devices that can be used to diagnose a disease or measure vital signs, to a new generation of surgical robots, we’re just at the beginning of seeing what’s possible when patients take control of their own healthcare data.
5. Chatbots: Taking Over Customer Support
Chatbots have been around since 1966, but they weren’t known as chatbots. The first iteration of a chatbot was designed to manage human conversations by responding to spoken or typed words. Today, we’re seeing these bots take over customer support roles on platforms like Facebook Messenger and Slack. By 2022, Gartner predicts that more than 85% of customer interactions will be managed without an actual human agent – just a bot powered by artificial intelligence and machine learning.
Conclusion
Artificial intelligence will play a pivotal role in everyday life over the next 10 years. Consumers who use chatbots and virtual assistants will continue to push technology forward, while big data, cognitive computing, and machine learning become even more critical business assets. As companies compete to advance technologies that improve lives around the world—and as these technologies spread into industries like health care and manufacturing—the potential for AI adoption only continues to grow. To make use of these technologies, get in touch with top machine learning development companies in India.
‘AI is a vital part of the fourth industrial revolution and will impact every aspect of people’s life’- Fei Fei Li, Professor at Stanford University.Artificial Intelligence has been one of the most reformative technological inventions in the history of humankind as it has made information systems more adaptive for humans.
Over the years, AI has played a definitive role in redefining different industry sectors & sections and the insurance sector in this context has a similar story as well.We need no superlative analysis to understand the importance of medical insurance, especially in the present turbulent times of the global pandemic.
Artificial Intelligence (AI) and Machine Learning (ML) have proved to be a vital cog that has streamlined end-to-end claim settlement, thereby increasing customer satisfaction.
The mediclaim management process can now be done faster and better with fewer or no errors.Gartner, in 2016, predicted that almost 1/3rd of the companies on a global level would use AI in at least one aspect of their sales process by 2020.
Moreover, there have been cases where the mediclaim insurance companies have instigated investigative operations to find the genuineness of the claim done by the policyholder.
Through in-depth data analytics, insurers can automate the process of fraud detection.It helps them to pre-assess the claims while simultaneously automating the damage evaluation process.After understanding the changes in brief that Artificial Intelligence (AI) and Machine Learning (ML) has brought in the insurance sector, we now dig deep to see the role these two techniques play.Role of AI and ML in the health insurance sectorThe expansion of AI and ML in different industry sectors, especially in the last decade or so has opened new avenues for the insurance industry and has allowed the insurers to provide a better customer experience.
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Like every other industry, data has also been the core of the insurance industry.
Over the due course of time, what actually has changed is the amount of data and the speed at which machines are processing it for driving useful insights.
Data-driven insights play a vital role in boosting this industry by making decisions based on facts, figures, and user patterns.
Insurance providers adopt Artificial Intelligence (AI) & Machine Learning (ML) technologies to enhance the end-user experience, develop improved solutions for increasing operational efficiency, and build accurate underwriting models.Machine Learning is an application of Artificial Intelligence technology that allows computer systems to deploy algorithms for learning and improving my experience.
Such algorithms are used for building mathematical models which can be used as training data, allowing systems to make decisions & predictions.AI & ML in Insurance IndustryAI and ML technologies make it easier for insurance providers to use the data at their desired pace and way.
Many organizations in this industry have access to data that is usually structured and stored in databases.
