Why AI at Scale is relevant to businesses
Early-adopting organizations are starting to see AI at Scale transform business functions. For example, in product development, companies are using it to track millions of data inputs from social and online activity to discover new consumer trends. Combining these insights with their internal product catalogues they’re able to use AI to identify potential gaps in their product offerings and make recommendations to expand into new markets altogether based on the latest trend data.
Likewise, we’re seeing successful use cases in customer service, where virtual agents can handle complex questions, resolving issues faster and doing so 24/7. In marketing, our large-scale AI models’ nuanced grasp of text, video and images create trustworthy, original and impactful content, including blogs, ad copy and emails. Also, other scenarios include finance, where models detect fraud across fraud protection networks; strategy, where they’re used to summarize content to assess competitors; and software development, where these models help developers code faster.
AI at Scale in action
Some early deployments of AI at Scale have been in industries tackling significant business challenges. Take, for example, healthcare, where current projections show medical knowledge doubling every 73 days compared to every three-and-a-half years in 2010. AI at Scale is being used, among other things, for clinical research and information management, with organizations customizing our large natural-language models with the latest data from clinical trials and medical publications. This significantly improves their ability to search and gain insight over vast amounts of information, accelerating the research and discovery process.
PhactMI, a non-profit collaboration of over 30 pharmaceutical companies including Novartis, GSK and AstraZeneca, uses the technology to improve document search and summarization. This helps medical information professionals produce faster response documents to healthcare providers’ pharmaceutical inquiries. It’s part of phactMI’s mission to support healthcare professionals provide quality patient care.
And software company AvePoint is using the Microsoft Turing model to create a personalized learning experience for its team members, extracting key knowledge across its product guides, release notes and customer support history, and unstructured data. The result: AvePoint is creating unique learning guides and testing materials for each employee. Given today’s business climate, onboarding new employees has never been more important, and the latest advancements in AI at Scale can help by creating and updating training processes, summarizing learning resources and customizing training plans for new joiners.
Whether you’re looking to improve product development, speed up research and reasoning over vast amounts of information or identify your company’s future growth areas, there are three simple steps to take.
First, think about where these capabilities can have the most immediate impact on your business. Maybe it’s in your product lifecycle, or in optimizing your marketing campaigns. Perhaps it’s in helping with your growth strategy. Microsoft AI Business School, an online series designed to help leaders develop a holistic approach to AI, provides frameworks and guidance to identify AI use cases, evaluate AI investments and more.
Next, formulate a strategy with a clear business outcome for leveraging advanced AI models to power natural language understanding and generation within your products and services. You can do this with a pilot project by accessing the models through Azure Cognitive Services, Azure Cognitive Search and the new Azure OpenAI service.
And third, no matter where you are in your AI and innovation journey, it all starts with learning. Learn more about how businesses accelerate innovation and build competitive edge with AI at Scale.
Take advantage of next-generation AI and start unlocking innovation opportunities for your business today!