AI Adoption Surges in 2019 Amid Data Bias Concerns
Artificial intelligence deployment among organizations more than triples in 2019, driven by accessible development frameworks and chatbot integration. However, growing awareness of data bias and a demand for explainable AI decision-making remain significant hurdles.
Artificial intelligence deployment among organizations grows significantly in 2019, jumping from 4% to 14% according to Gartner’s CIO Agenda survey. Companies rapidly integrate AI into their operations by utilizing smart speakers like Alexa and Google Home as new marketing channels, while also deploying chatbots to handle common customer service queries in place of traditional call centre staff.
The barrier to entry for AI development remains quite low due to the widespread availability of modern AI frameworks, allowing developers to easily build intelligence into their software applications. However, data quality emerges as the primary stumbling block for businesses, as inaccurate or unrepresentative datasets inevitably lead to flawed data models and poor AI decision-making.
Throughout the year, there is a growing awareness regarding the inherent biases found within training datasets that negatively impact minority groups. This recognition drives a strong push for explainable AI, particularly in the public sector and regulated industries, where organizations now demand clear explanations for how artificial intelligence systems arrive at their conclusions.