Steps to Taking AI to the Next Level in Retail
Use this step-by-step guide for using edge computing to successfully deploy artificial intelligence (AI) solutions that can boost sales, improve customer and employee experience, and empower better decision making.
Data-centric solutions result in highly personalized customer experiences and product recommendations, accurate forecasts, inventory efficiencies, more secure premises and smarter business overall. But while the benefits of combining data gleaned from sensors, cameras and other edge devices with AI and advanced analytics are clear, retailers may be struggling to identify where and how to start and how to ensure success. In fact, experts find that the overall failure rate of AI projects (across all industry verticals) is somewhere between 83% and 92%.1 Following the steps outlined in this implementation guide can assist retail organizations to maximize their chances of a successful journey to edge computing and AI adoption and all its benefits.
Retailers can take a three-phase approach to a successful edge computing and AI adoption strategy:
Phase 1: Prepare Well
Follow these preparatory steps to lay the foundations for AI success.
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Phase 2: Prove Business Value With Your First AI Project
With the groundwork complete, take these steps to prove the business value of your initial AI project.
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Phase 3: Scale Your Success
You’ve completed your pilot project, now it’s time to scale.
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Let Intel Help You on Your AI Journey
To help companies harness the transformative power of the IoT, Intel® offers a broad portfolio of tested and proven Intel® IoT Market Ready Solutions and Intel® IoT RFP Ready Kits that deliver business results today, while laying the foundation for an even more connected tomorrow. Each of these scalable IoT solutions is vetted for completeness, repeatability, and scalability, and designed to tame the complexity of IoT solution development and implementation.
Product and Performance Information
Fortune, July 2022, “Want your company’s A.I. project to succeed? Don’t hand it to the data scientists, says this CEO.”