AI is no longer experimental but the cornerstone of success if companies don’t want to fall behind their competitors. 84% of decision makers agree that their businesses must implement AI to maintain a competitive advantage in their industry. , moreover almost half of technical leaders expect AI to play a critical strategic role in their business. Those companies that have implemented and use AI in applications have already gained a number of benefits, such as better customer experience, increased automation, employee productivity growth, enhanced business agility, and revenue growth.
While the possibilities for AI within applications are endless, companies should focus on five use cases where AI’s value has already been proven.
AI-powered knowledge mining first analyzes documents with AI to structure content. It can then sift through all this information at a digital speed and make it available to anyone via a search query or even an application-initiated, automated search to proactively serve the user.
Document process automation
AI in the form of OCR for text extraction combined with natural language processing for understanding can pull important information to automate actions in business processes and route to the right people to handle exceptions.
Speech transcription and analytics
AI listens and transcribes people’s speech into the written word, even more some AI services can provide analytics to add important context to the transcription such as number of minutes logged per speaker.
AI understands and almost instantly translates popular spoken languages from one to another, making cross-region business more accessible.
Conversational AI enables enterprise developers to create rich, contextual digital assistants to speed up the discovery of information for both customer and employee use cases.
Most companies are not using AI in the majority of their applications but given the growing number of AI capabilities and use cases to deploy, the number of apps using AI is expected to grow substantially. The key challenge for companies is to implement these functions faster than competitors, because AI can play a critical role in driving application innovation and competitive differentiation. Technical decision-makers ideally want to see at least 55% of their core business applications and customer-facing applications leveraging AI functionality. However, technical leaders grapple with three primary challenges when building AI: lack of quality data, lack of proper application development skills, and lack of proper data science and machine learning experience.
The road to AI doesn’t need to be burdened with advanced data requirements and endless development cycles. Professional IT solutions and service providers like Softline have the expertise and experience to drive through your company on this road. Contact our team and we help you to simplify and strengthen the deployment of AI in applications and gain all the benefits of AI.
Enterprises are implementing a new generation of machine learning operations (MLOps) platforms that help them democratize and operationalize AI, allowing them to accelerate and govern the end-to-end machine learning (ML) model lifecycle. In this article we collect the drivers why organizations decide to develop Machine Learning model, and we summarize why Microsoft Azure Machine Learning is the solution.
Računarstvo u oblaku ima jasnu ulogu na putu kroz digitalnu transformaciju, ali možda neće svakoj kompaniji biti očigledno kako se efikasno realizuje. Saznajte koje ključne tačke treba uzeti u obzir pre i tokom tranzicije i započnite odmah novo poglavlje u životu svoje kompanije.
Manufacturers globally are being disrupted and moving from making products to delivering products-as-a-service. To compete and grow, manufacturing companies need to shift their focus from engineering and production to customer outcomes. In this article we summarize those four key transformation topics that can help manufacturers stay competitive while meeting changing customer needs based on Microsoft’s ebook.
The world is changing. Manufacturers need to transform the way they work. Up to 2.4 million manufacturing jobs could remain unfilled between 2018 and 2028 due to inadequate skills. The structure and execution of talent processes will need to be re-thought and built around the realities of a likely protracted and uneven recovery, to continue achieving desired business outcomes as well as inclusive employee experiences. Read the summary of Microsoft’s ebook called “Facing the Future of Manufacturing” and learn how manufacturing companies can move confidently into the next normal.