Beyond productivity: How industry-specific AI fuels growth
With AI adoption on the rise, companies around the world are saving time, streamlining tasks, and analyzing information faster. Here at Microsoft, we see firsthand how our customers are boosting productivity and focusing on higher-value work with Microsoft Copilot.
Now, the focus is starting to shift. Productivity gains are just the beginning of a broader transformation—one that goes beyond efficiency to reshape industry processes, decision-making, and customer experiences.
True AI transformation requires an industry perspective
In our conversations with customers, many are asking about the next wave of AI. They’re ready to expand beyond general AI applications and invest in solutions tailored to their specific challenges. While organizations recognize AI’s value and potential, it must address industry-specific needs to deliver the biggest results.
Take healthcare, for example, where engaging with patients requires sensitivity, data privacy, and personalized care. That’s very different from retail, where personalization is all about tailored shopping recommendations and seamless experiences.
The same contrast exists in manufacturing and transportation. Manufacturers focus on optimizing production lines for efficiency and quality, while fleet operations prioritize logistics, route optimization, and fuel costs.
These differences show why AI adoption is moving beyond general-purpose tools to industry-specific solutions that drive even greater impact. In our recent video series on the Return on Investment (ROI) of AI, we explore this trend, real-world use cases, and how AI is transforming industries like financial services and retail. These insights reflect what I’m seeing in conversations with customers about the changing AI landscape.
Where to invest in AI for maximum impact
Today’s leaders are looking beyond AI for productivity and asking a bigger question: Where should we invest next to drive business growth? The key is to align AI investments with mission-critical priorities.
So, is the AI for industry buzz real, and is it worth the investment? The answer is yes—here’s why:
- Industry-specific AI solutions tackle complex challenges—such as regulatory compliance in financial services, seamless omnichannel shopping experiences in retail, and asset troubleshooting in manufacturing. At Microsoft, we’ve worked with thousands of customers to identify industry use cases where AI delivers meaningful business results. Building on these insights, we offer customizable AI agents designed to accelerate time to value for our customers.
- Customizable AI agents in Microsoft Copilot Studio help businesses tailor AI to their needs. Agent Builder, a feature within Copilot Studio, simplifies customization with industry-specific knowledge and low-code tools. In addition, our customers have access to a wide range of adapted AI models to accurately and effectively address their unique needs.
- AI models, developed in collaboration with partners, and built for specific industries make adoption easier across every sector and region. These fine-tuned models are trained on industry data to support business-critical use cases.
To see industry-specific AI in action, let’s explore key use cases in financial services, retail, manufacturing, and healthcare.
Driving growth in financial services with AI
Financial services organizations are leading the way in AI adoption, and it’s paying off. They’re realizing a 4.2 times average ROI on generative AI initiatives1—the highest across industries. Discover how PicPay uses Microsoft AI to answer product and service questions quickly and securely.
Key use cases for AI in finance industry include:
- Banking: AI enhances customer interactions, improves fraud detection, and streamlines meeting preparation.
- Insurance: AI speeds claims processing and resolution, identifies upsell opportunities, and improves customer engagement.
- Capital markets: AI personalizes client presentations, generates predictive insights, and accelerates research.
Watch the video to explore AI business transformation in financial services.
Retailers solve complex challenges with AI
Retailers are realizing a 3.6 times ROI on generative AI initiatives,2 and some are tackling customer acquisition, profitability, supply chain reliability, and data complexity. Learn how ASOS, a British online fashion retailer, uses Azure AI Foundry to surprise and delight young fashion lovers with engaging, inspirational experiences.
Key use cases for AI in retail industry include:
- Personalized Shopping Agent engages in natural language conversations, delivering tailored recommendations and assisting with specific requests.
- Store Operations Agent integrates product search, inventory, orders, omnichannel pricing, and incident management into existing applications.
- AI-powered insights help retailers create targeted marketing campaigns that boost engagement and increase sales. See how Microsoft Cloud for Retail connects customers, employees, and data.
Watch the video to see why the retail industry is embracing AI.
How AI powers smarter manufacturing
Manufacturers are achieving a 3.4 times ROI on generative AI initiatives.3 They’re also using AI to speed time to market, streamline application lifecycle management, and simplify manufacturing processes. See how Schneider Electric addresses the company’s most pressing issues by innovating with Azure OpenAI Service.
Key use cases for AI in manufacturing industry include:
- AI-powered generative design accelerates product development by automating design processes, refining models in real time, and freeing teams to focus on manufacturability and compliance.
- AI-assisted coding helps developers write, debug, and optimize code faster, enhancing industrial software development and connected product functionality.
- AI-powered factory insights provide real-time data for root cause analysis, production loss reduction, and asset maintenance, boosting efficiency and safety.
Learn more about Microsoft technology in the manufacturing industry.
AI helps empower the healthcare workforce and enhance patient care
In healthcare, AI is transforming medical data management, personalizing clinician and patient experiences, and helping to improve patient outcomes—delivering a 3.3 times ROI on generative AI initiatives.4 See how AI innovation empowers healthcare teams to refocus on the clinician-patient connection at Northwestern Medicine, Overlake Medical Center & Clinics, and Atrium Health.
Key AI use cases for healthcare include:
- AI assistants help streamline clinical documentation, surface information, and automate tasks to improve efficiency, satisfaction, and patient care.
- Advanced healthcare AI models are designed to enhance disease detection, diagnostics, and treatment planning.
- Multimodal AI generates insights from unified healthcare data to identify care gaps faster for early intervention, develop more tailored care plans, improve the accuracy of diagnoses, and allocate hospital resources more effectively.
We’re here to help you drive AI success
Organizations that invest in industry-focused AI applications and stay current with AI industry trends are realizing the greatest ROI with AI. We’re here to help you take action now and position your business for innovation, efficiency, and competitive advantage.
Watch the ROI of AI video series to learn more about AI ROI.
1, 2, 3, 4 IDC InfoBrief: sponsored by Microsoft, 2024 Business Opportunity of AI, IDC #US52699124, November 2024.
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Source: Microsoft Industry Blog