Nowadays, organizations adopt artificial intelligence (AI), as it propels them on the fast track to innovation and productivity.
According to “IDC Worldwide Storage for Cognitive/AI Workloads Forecast”, 2018-2022, 40% of digital transformations were expected to use AI services by 2019 and the total IT storage spend for AI was estimated to $4.79 billion in 2019.
However, organizations continue to be faced with multiple challenges when supporting AI development teams or deploying and scaling production AI workloads. Data volume and quality, advanced data management, and a skills gap are among the core challenges organizations face when supporting AI development teams or deploying AI workloads.
One very important aspect to consider is the information architecture, key to the efficiency of your AI pipeline. The AI pipeline - how you ingest, organize and analyze data and, ultimately, train models to create AI-driven insights from that data - is essential to efficient data science.
Moreover, AI projects are easier and more likely to succeed if they’re built on a solid foundation. IBM Storage for AI provides that foundation, with a collection of offerings that put you on the fast track to AI productivity by addressing the top business challenges associated with deploying AI workloads.
It's no secret that harnessing the power of your data provides a significant competitive advantage. AI enables you to easily unlock the value of that data and transform your business in innovative new ways, including predicting and shaping future outcomes, optimizing your workforce to engage in higher-value work, automating processes and reimagining business models.
Set off on the journey to AI with a single successful proof-of-concept, and it will quickly grow across the organization. The right storage platform must deliver performance, scalability, and flexibility, which AI projects demand.
Find out more about AI and big data from our ebook, “Storage for AI: The fast track from ingest to insights”. IBM Storage delivers a guide to AI and big data, which will enable you to tackle top challenges when adopting AI, address the challenges of your AI pipeline with the right IT infrastructure, harness the power of your data using AI.
