Fuel Application Innovation with AI Cloud Services
In a rapidly evolving digital landscape, leveraging AI is crucial for organizations to stay competitive. The Microsoft-commissioned Forrester report, "Fuel Application Innovation With Cloud AI Services," explores five use cases for implementing AI in the cloud and enabling businesses to quickly realize value and drive innovation. Discover how knowledge mining, document process automation, speech transcription and analytics, machine translation and conversational AI can reshape your applications and create a competitive edge. Discover 4 key findings based on an online survey of over 500 technical decision makers responsible for AI implementation at their companies. Gain insights into implementing AI without the need for a large data science team. Download the report now to fuel your application innovation.
Why is AI important for businesses?
AI is increasingly seen as essential for business success. According to a survey, 84% of technical decision-makers believe that implementing AI is crucial to maintaining a competitive edge in their industry. More than 70% recognize that AI has real business value, and over 40% expect it to play a critical strategic role in their operations.
What challenges do organizations face in implementing AI?
Organizations face several challenges in AI implementation. About 64% of technical decision-makers lack confidence in meeting their AI goals due to insufficient resources. Key challenges include data integration issues (60%), lack of quality data (43%), and long development times (51%). Additionally, many believe that specialized development skills are necessary, which can hinder progress.
How can cloud AI services facilitate AI adoption?
Cloud AI services provide prebuilt, configurable AI capabilities that simplify the integration process for developers. They allow organizations to bypass extensive modeling work and deploy AI functionalities quickly. Approximately 45% of technical leaders see using cloud AI services as a key step toward better AI deployment, enabling faster implementation and reducing reliance on specialized skills.
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