Last week, companies all around the world came together at Microsoft Ignite to look at how technologies are transforming business, and one technology took center stage. You guessed it: gen AI (artificial intelligence). IDC suggests gen AI usage jumped from 55% in 2023 to 75% in 2024 and worldwide spending will reach $632 billion by 2028. For today’s blog, let’s take a look at some powerful case studies and what’s in store for 2025 and beyond.
To start, let’s better understand the impact of gen AI in particular. For decades, companies have been working with structured data, which is typically just 10% of the data available. But now, gen AI has opened up the other 90% of data, which is unstructured.
McKinsey & Co., predicts by 2030, companies will be approaching data ubiquity, as data will be embedded in systems, process, channels, interactions, and decision points that drive automated actions. With data volumes expected to increase by more than 10 times from 2020 to 2030, capturing and leveraging that data is going to be key.
This is where Microsoft Ignite comes into play. Here we saw the opportunities that gen AI brings—and specific examples of how companies are leveraging it in a way that is impactful. Let’s look at just a few examples.
Manufacturing and operations automation provider ABB Group is using generative AI to help industrial-sector customers better manage their carbon footprint. The company turned to Microsoft Azure OpenAI Service to build Genix Copilot, a generative AI solution that integrates with its core Genix industrial IoT and analytics suite to answer customer questions in natural language and provides specific, actionable insights.
The results of leveraging this technology are very powerful. ABB says this proactive approach can help customers see up to 40% cost savings in operations and maintenance, a 30% boost in production efficiency, and a 25% improvement in sustainability. The new solution is also helping ABB’s own teams improve the way they work.
As another example, logistics platforms company C.H. Robinson has automated is email price quoting system using Microsoft Azure AI to significantly reduce response times for more than 2,000 daily pricing requests from shippers. The company’s automated AI system now classifies incoming email, uses generative AI to piece together the details in it, then replicates the steps a person would take to fulfill the customer’s request. This automation has reduced email quote times from hours to just 32 seconds, freeing employees for more valuable tasks.
The big value here is being able to capture greater efficiencies in global supply chains. Research from Gartner suggests AI and gen AI are top digital supply chain investment priorities. We see 26% of North American respondents identified AI, including machine learning, as their top digital supply chain priority.
As yet another example, Toyota Motor Corp., used Microsoft Azure OpenAI Service, Azure Functions, and Cosmos DB to build a system of generative AI agents to store and share internal expertise with the goal of developing new vehicle models faster. Toyota says its powertrain engineering team uses the new solution hundreds of times a month.
Of course, these are only a few examples from Ignite. All in all, there are big opportunities on the horizon with gen AI. IDC suggests for every $1 a company invests in generative AI, the ROI (return on investment) is $3.7 times. When will your company begin to tap into the opportunities gen AI offers?
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