Artificial Intelligence (AI) is customized software meant to mimic the cognitive functions of the human brain to solve problems and achieve goals. Businesses and organizations are adopting AI, most commonly investing in automation for customer service needs—for example, virtual assistants, chatbots, etc. Other popular reasons for implementing AI include social data mining, human resources automation, enhancing products and services, and translating languages (i.e., Google Translate). Still relatively new, AI adoption is growing across the world among organizations looking to streamline processes and raise efficiency and production standards. AI adoption is the most popular in telecom, high-tech, and financial services industries.
AI has been evolving since the 1950s, and a wide range of initiatives have developed over the past few decades. Machine learning (ML) is currently the most popular form. Computers use a massive set of data and apply algorithms to teach themselves and make predictions. Natural Language Processing (NLP) works with ML to decipher human language into programming for chatbots and other virtual communications systems.
Although AI adoption is becoming popular, it has a few key challenges in its still-early stages. For AI to function, a large volume of relevant data is required, which not all organizations and industries have collected. Organizations struggle to hire AI experts, as it is an emerging field, and talent with AI skills is hard to find. Data privacy and cybersecurity breaches are also a concern for organizations when implementing AI.
Organizations and businesses are benefitting from AI adoption. Here’s how:
Accelerate change for a promising future with AI-ML solutions