How Business Leaders Can Take AI Past the Test Phase

AI is transforming businesses everywhere with improved process efficiencies, customer experience, and employee productivity. Excited about new possibilities, organizations are eagerly integrating artificial intelligence into their business strategies. According to McKinsey, half of businesses say they have adopted AI.

But, despite the excitement, there are still many barriers to adoption. According to IBM, these barriers include lack of AI skills and expertise (34%), cost (29%), lack of tools and platforms (25%), complexity to integrate and scale (24%), and data complexity (24%). Enterprises have tried to address these challenges in a myriad of ways, leading to varying success with AI. Instead, what is needed is a structured approach that begins by understanding the business needs and the AI requirements to support it.

Launching any AI project requires a significant investment of resources. With this commitment of time and money, businesses need to make sure they don’t make it any more complicated. To simplify their AI journey, business leaders should focus on what problems they’re trying to address to better zero in on what AI foundations—be it model development, improved latency or data integrity—they need to focus on.

Intel helps organizations minimize complexity by enabling them to integrate AI into the open-standards tools they already use. Intel has a large portfolio of software to help developers accelerate their AI journey, including hundreds of pretrained AI models and reference kits. An active participant of and contributor to hundreds of open source projects, Intel has optimized software directly into popular software frameworks like Pytorch and Tensorflow. 

Intel also empowers developers to streamline their AI efforts with the 4th Gen Intel® Xeon® Scalable processors, which help businesses leverage and scale their AI from day one. These processors have built-in AI accelerators that speed up training and inference. Instead of requiring the purchase of additional hardware for every use case, the processors’ deep learning capabilities enable companies to easily build out the most popular AI use cases, like natural language processing (NLP), chatbots, recommendation systems and image recognition.

To operationalize AI from concept to production, business leaders need the hardware and software portfolio to help them deploy from anywhere, faster. Intel has solutions for every leg of the AI journey, starting with open source software for the AI pipeline, all the way through to data processing, model development and deployment. One Intel tool that increases efficiency is OpenVino, which allows developers to write one set of code and deploy it anywhere that’s needed. OpenVino also supports deep learning models including the large language models.

Organizations also need to ensure they think through their cyber strategy as they scale their AI, leveraging partners that put security first. Using confidential compute technology, Intel ensures data is encrypted, that access to sensitive data can be better protected, and that multi-party AI models can be built without accessing other party’s data.

While AI can help businesses improve revenue, efficiency and productivity, scaling the technology is also a journey. Intel’s robust hardware and software solution portfolio helps ensure it is a successful one.