Global Big Data Conference

Enterprises are increasingly looking to AI for opportunities to boost revenue as their operations move online. According to a 2021 PricewaterhouseCoopers survey, a quarter of companies report widespread adoption of AI in their organizations -- up from 18% in 2020. But AI projects are at risk of stalling due to the many roadblocks businesses encounter on the pathway to implementation. In a Gartner report, analysts estimate that 85% of AI projects will deliver erroneous outcomes -- whether due to bias in the data and algorithms or the teams managing them. An emerging discipline called machine learning operations, or MLops, aims to prevent these failures by combining machine learning, devops, and data engineering to facilitate the deployment and maintenance of AI models.