… by a proprietary machine learning model which takes into account privacy policy length, structure of the website, description of data uses, …

Over the last several years, the use of artificial intelligence (AI) and machine learning (ML) has maintained consistent growth among businesses. During our 2017 survey of IT decision makers in the United States and Japan, we discovered that approximately 74% of businesses in both regions were already using some form of AI or ML to protect their organizations from cyber threats. When we checked in with both regions at the end of 2018, 73% of respondents we surveyed reported they planned to use even more AI/ML tools in the following year. For this report, we surveyed 800 IT professionals with cybersecurity decision-making power across the US, UK, Japan, and Australia/New Zealand regions at the end of 2019, and discovered that 96% of respondents now use AI/ML tools in their cybersecurity programs. Despite the increase in adoption rates for these technologies, more than half of IT decision makers admitted they do not fully understand the benefits of these tools.

Microsoft has explained before that it uses PC "telemetry" information and machine learning to assess the readiness of PCs for Windows 10 feature upgrade releases, which arrive twice per year. In a blog post this week, Microsoft data scientists Archana Ramesh and Michael Stephenson expanded on how the company uses machine learning algorithms to ensure those feature upgrades are rolled out successfully at organizations. Background A Windows 10 feature upgrade essentially replaces the underlying operating system's bits with a new OS version. The process is called an "in-place upgrade." However, there are lots of potential issues that can arise with each OS upgrade, given the variations in hardware, drivers and software that exist, as well as flaws that may be present in the upgrade itself. Some Windows 10 upgrade releases have been minor disasters.

Microsoft this week unveiled a new service that integrates its Azure platform with a globally distributed streaming analytics solution. Now available in preview, Azure Databricks is designed to help app users and developers take advantage of machine learning, graph processing and AI-based applications. It was one of many announcements made by Microsoft during the opening keynote of its annual Connect() developer conference, which kicked off Wednesday in New York City. Azure Databricks will enable organizations to build modern data warehouses that support self-service analytics and machine learning using all data types in a secure and compliant architecture, according to Scott Guthrie, Microsoft's executive vice president of Cloud and Enterprise, speaking at the the Connect() keynote. Databricks is the creator and steward of Apache Spark.

Microsoft this week unveiled Bing for Business, a new deliverable that will put Bing at the center of Microsoft's enterprise search and artificial intelligence efforts. Bing for Business is a product of Microsoft's 1-year-old AI research group. Led by Executive Vice President Harry Shum, the group comprises the Microsoft Research organization and the company's Bing, Cortana, Ambient Computing and Robotics, and Information Platform units. Bing for Business brings the Microsoft Graph to the browser, allowing employees to perform personalized and contextual searches that incorporate interfaces from Azure Active Directory, Delve, Office 365 and SharePoint. Li-Chen Miller, partner group program manager for AI and Research at Microsoft, demonstrated Bing for Business during the opening keynote session at this week's Ignite conference, showing how to discover an organization's conference budget.

Dynamics 365, a new cloud service from Microsoft that combines components of its CRM and ERP offerings, will become available on Nov. 1, the company announced Tuesday. First unveiled in July, Dynamics 365 is a set of apps for seven CRM and ERP functions: financials, operations, marketing, sales, customer service, project service automation and field service management. Organizations can purchase each Dynamics 365 app separately, adding more as their needs change. They also have the option to purchase a set of apps as a subscription bundle. Microsoft announced one such app on Tuesday called "Dynamics 365 for Customer Insights."

At Microsoft's Build conference on Wednesday, CEO Satya Nadella laid out his company's vision for the future of artificial intelligence (AI) and machine learning. Microsoft has already made plain its ambitions to make Cortana and its machine learning-based engine more useful and pervasive. Nadella elaborated on those ambitions during Wednesday's Build keynote, describing Microsoft's concept of "conversational computing" and how it will be integrated in everything from Windows, its Edge browser, Outlook and Skype, to the entire ecosystem of software, hardware and cloud-based SaaS offerings. Nadella sees conversational computing using speech as the next user interface and framework for how all applications are developed and connected. In a callback to the name of the conference, Nadella called on developers to "build" the next wave of applications based on tools and services that Microsoft is rolling out, including 22 Cognitive Services APIs for the Azure-based Cortana Intelligence Suite (previously called the Cortana Analytics Suite) and the new Microsoft Bot Framework.

CEO Satya Nadella's 1 billion security initiative yields fruit with the Azure Security Center, powered by the technology behind Azure Machine Learning. Microsoft CEO Satya Nadella late last year outlined the company's 1 billion investment in a new, holistic, operations-centric approach to addressing cybersecurity with the formation of its Enterprise Cybersecurity Group (ECG). Until this point, the Trustworthy Computing Initiative launched in 2002 by co-founder Bill Gates was largely at the center of the Microsoft security universe. That paved the way for the Security Development Lifecycle (SDL) -- the companywide blueprint for how all of Microsoft's software would be architected, built and maintained. Consequently, SDL is baked into the Microsoft delivery model, and new versions of products ranging from SQL Server to Windows are markedly more secure than the last.