AI and machine learning have emerged as modern, vital ways for organizations to get ahead. Many businesses today prioritize data, analytics and AI/machine learning projects to power new business models, enhance product and service offerings, improve efficiency, drive revenue and deliver superior customer experiences.
Gartner predicts that under half of modern data analytics and machine learning projects will be successfully deployed in production by 2022.
Less than a fifth will move piloted AI projects into production without delays caused by a range of problems – from technical skills gaps and lack of IT/business process maturity, to insufficient organizational collaboration.
This combination of pressure and challenges can overwhelm your business, especially if you’re at the start of your AI and machine learning journey.
Business benefits follow, such as analyzing data sets that are too large for humans to process, answering questions in real time that draw from existing data and experiences, and automation that can reduce costs and boost productivity.
If you’re looking to machine learning and deep learning but have concerns about your existing data, be mindful that they don’t always need massive data sets.
You must think about what AI and machine learning can bring to your business and the most effective way to achieve that, thereby keeping your company ahead.
Is your business want to remove pain points using AI & Machine Learning?