1. Sentiment Analysis These tools can help you understand the emotions and opinions expressed in text data. Understanding the sentiment in data can be used to monitor and analyze customer feedback, as well as to understand social media trends. 2. Document Processing This can analyze text, provide semantic search or semantic reasoning, and automate the tedious and timeconsuming tasks of manual data entry and processing. Document processing tools can extract information from various document types, including PDFs, images and scanned documents such as invoices, financial statements and compliance reports. 3. Text Classification Text classification and topic modeling solutions automatically classify and organize your text data. It involves the process of automatically assigning texts to one or more predefined categories and can be used to sort emails, articles, customer reviews and other types of text data. 4. Natural Language Generation These solutions can automatically generate text from data and can be used to create reports and provide text summaries, descriptions and other types of text data. 5. Predictive Analytics Predictive analytics is a field of data science that uses historical data and machine learning algorithms to make predictions about future events and unlock the value in data. This technology is used across industries for various applications, such as identifying trends, predicting demand and making decisions about pricing and marketing strategies. 6. Demand Prediction Predictive models for demand prediction can help businesses forecast future demand for your products or services, optimize inventory levels and make better decisions about pricing and marketing strategies. 7. Churn Prediction Custom predictive models can help identify which customers are at risk of canceling their subscription, product or service. With this information, a business can target at-risk customers with personalized offers and benefits to make them stay. 8. Recruitment Intelligent recruitment and job-pairing solutions can help employers find the best candidate for a job. The system works by analyzing the profile of the job and the profile and resumes of the potential candidates, then uses machine learning algorithms to identify the best potential matches for the job based on experience and qualifications. With a powerful recommendation system, employers can quickly and easily identify the most qualified candidates for a job. 9. Predictive Maintenance Machine learning (ML)-driven predictive maintenance solutions can detect potential equipment failures before they happen. By using predictive analytics, you can avoid costly downtime and improve the efficiency of your operations. 10. Image Analysis and Segmentation Algorithms for image analysis and segmentation can help automatically detect and classify entities in images, extract specific features from images, and develop biometrics systems for facial recognition. 10 Ways AI Transforms Business EMERGENT While artificial intelligence often is generally thought of in terms of customer service chatbots and customized marketing, while increasingly moving into cybersecurity solutions, “its potential to benefit other key aspects of a business operation is seemingly boundless,” said Angel Vossough, data scientist, CEO and Co-Founder of BeterAI. “Data management and data analytics play a critical role in making organizations more efficient, driving visibility and accelerating growth,” she continued. “Those doing it well by leveraging AI can gain actionable insights and operational efficiencies that result in a significant informational edge –and competitive edge at large” In the interest of expanding the conversation with customers and helping partners think outside the AI-chatbot box, here are 10 ways that businesses currently are applying one subset of AI – natural language processing (NLP) – courtesy of Vossough and BeterAI. Angel Vossough 8 CHANNELVISION | SEPTEMBER - OCTOBER 2024
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