Five Common AI/ML Project Mistakes

Companies of all sizes and across all verticals continue to embrace artificial intelligence (AI) and machine learning (ML) for myriad reasons. They're eager to leverage AI for big data analytics to identify business trends and become more innovative, while also improving services and products. Companies are also using AI to automate sales processes, marketing programs and customer service initiatives with the common goal of increasing revenue. But the unfortunate reality is that 85% of AI and machine learning projects fail to deliver, and only 53% of projects make it from the prototype to production. Nevertheless, according to a recent IDC Spending Guide, spending on artificial intelligence in the United States will grow to $120 billion by 2025, representing growth of 20% or more.