Commercial AI and ML's increased practice will help in quicker deployment of models in the manufacture, driving more worth to business and investments.
FREMONT, CA: Data and analytics have continuously been apprehended as pivotal players in businesses for improving business competence over the years. Data and analytics are favorably viewed in recruitment, customer service, optimization of supply chains, finance optimization, and other purposes in different organizations. Therefore, it is required for data and analytics leaders to monitor, research, and emerging technologies actively.
It is also a wise move to pick on budding trends that will assist in streamlining and growing the business. Below is a list of the prime data and analytics trends businesses should consider keeping the company ahead of the game toward a more competitive future.
1. Commercial Artificial Intelligence (AI) and Machine Learning (ML)
AI and ML have incessantly played a vital role in developing different industries and is projected to become more commercial in 2020. Accordingly, commercial AI and ML's increased practice will help in quicker deployment of models in the manufacture, driving more worth to business and investments.
Even though the open-source has influenced AI and ML technology, having it commercialized will open doors to scalable solutions for model management, project management, data reuse, lineage, and transparency. In 2022, over 75 percent of new end-user solutions integrating AI and ML techniques are anticipated to be built commercially rather than offered in the open-source platform.
2. Conversational Analytics and Natural Language Processing
According to a research and advisory firm, it was predicted that by 2020, about 50 percent of analytical queries would be produced through search, voice and natural language processing fused into different applications for easy use and access. Voice-enabled equipment has become widespread in various industries due to its user-friendly interaction with clients and businesses.
The technology will continue to grow as a trend in the business data analytics sector. It offers integrated voice applications, and firms realize that conversational analytics brings substantial benefits, including improved social listening, sentiment analysis, and personalization.
These factors are a huge aid in the practice of conversational-based interfaces and chatbots. Equally, the insights are better carried through conversational analytics by communicating data through AI-driven combinations of Natural Language Generation (NLG) and Natural Language Processing (NLP).