AI-empowering processes for building an intelligent enterprise

At the ongoing AI Summit in Hong Kong, Ms. Ling Yi Chang, AI/ML Specialist, Microsoft, presented on the AI-empowering processes for building an intelligent enterprise.

The cloud is making resources available and salable for businesses. It enables companies to access to enough compute power, massive amount of data and pre-trained models. This significantly increases efficiency and security. Cloud optimises storage, networking and security, and reduces costs. You can scale up and down, easily, for heavy computing tasks, as needed.

Processes are everywhere! There are HR, industry, finance, procurement, departments that are interacting with government, logistics, manufacturing, medical, oil and gas, etc. There is a process intelligence framework. AI capabilities can digitalize them. Eg., there is the OCR to read your document. We also have language understanding for documents. There is translation as well.

How can we leverage the existing stuff into the new areas? There are the power platform, power BI, SharePoint, Office AI builder, AML, etc. There needs to be automation, followed by visualization. The goal is to strengthen collaboration. It depends on the data estates. That will enable you to make better data-driven decisions. Besides BI and analytics, there is also RPA platform integration or process automation.

The enterprise bots is also about how it will solve the problems. The knowledge advisor is the ultimate goal. We need to take data and convert to very strong knowledge. It can help us build an intelligent platform.

Digitalization gives you another pair of eyes and ears. You also need vision, in terms of computer vision, read/OCR, etc. An example is from a manufacturing company approach. They are doing PO reading using form recognition.

Next comes automation. Robots, humans and AI are working together to accomplish a mission. You can also build apps faster than before, using Azure DevOps. You can standardize data and collection. Consume data and analytics results. There is single place for collaboration.

Visualization needs to have a view of everything. It shows different data coming in from every place. Azure ML democratizes, accelerates and scales AI. Also, there are more personas building AI apps. Azure ML is one place to manage your ML lifecycle end-to-end.

How can we make an FAQ assistant to a knowledge advisor? We can have a data platform with cognitive services/search, and biz apps, along with conversational AI. The process intelligent platform can help build a data-driven organization.