In this edition of Voices of the Industry, Jim Carson, Data Science Manager at Service Express, shares how natural language processing techniques can automate tasks and increase accuracy in your organization. The future of the data center will rely heavily on artificial intelligence (AI) and machine learning (ML) to improve business processes. As mentioned in our previous article, Streamlining Data Center Tasks With Machine Learning, many CIOs and technology leaders are already adopting an AI strategy in their IT departments. One ML technique that stands out as a focus of recent adoption in the data center due to its unique capabilities to analyze unstructured text data is natural language processing (NLP). According to IBM's Global AI Adoption Index, around half of organizations are using applications powered by NLP and over a quarter expect to implement them over the next year.

In this edition of Voices of the Industry, Service Express Chief Technology Officer Jake Blough shares how machine learning offers new opportunities for IT leaders to accomplish routine tasks in the data center. Digital transformation in IT departments enables businesses to take advantage of artificial intelligence (AI) and machine learning (ML) to streamline tasks and improve operations in the data center. The key to understanding the distinction between AI and ML is to view automation as an umbrella with artificial intelligence, machine learning and deep learning as subsets of automation. AI is broadly defined as a technique that mimics human behavior. Machine learning uses data and algorithms to understand and improve from experience over time.