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During its Think conference this week, IBM unveiled AI-driven products across its portfolio of enterprise platforms. Mono2Micro, a new capability in WebSphere, taps AI to streamline cloud app migration. Watson Orchestrate helps automate work in business tools from Salesforce, SAP, and Workday. And an updated IBM Cloud Pak for Data ostensibly reduces the cost and complexity of curating data for AI and machine learning workloads.
The AI industry is booming, with research commissioned by IBM finding that almost a third of businesses are using some form of AI and machine learning. By 2027, the global AI market is expected to be worth $733.7 billion, according to Grand View Research. But while recent advances in the technology are making AI more accessible, a lack of skills and increasing data complexity remain top challenges.
The new Mono2Micro service in WebSphere Hybrid Edition, IBM’s app and integration middleware, optimizes apps and workloads to run in hybrid cloud environments on Red Hat OpenShift. Mono2Micro refactors apps to move them to the cloud, restructuring existing code without changing its behavior or semantics.
IDG reports that the average cloud budget is up from $1.62 million in 2016 to a whopping $2.2 million today. But cloud adoption continues to present challenges for enterprises of any size. A separate Statista survey identified security, managing cloud spend, governance, and lack of resources and expertise as significant barriers to adoption.
“As IT complexity grows with increased adoption of hybrid cloud, enterprises are looking to bring in the power of AI to transform how they develop, deploy, and operate their IT,” IBM wrote in a blog post. “A significant challenge CIOs face is that many of their core applications were written for an on-premises world and they can have hundreds to thousands of legacy applications that need to be modernized and moved to the cloud.”
Mono2Micro uses machine learning and deep learning to analyze large enterprise Java applications. The analysis produces two alternative refactoring options for an application that can be explored in graphs and reports for transparency and explainability.
The newest member of IBM’s Watson family, Watson Orchestrate, is designed to give workers across sales, human resources, operations, and more the ability to perform tasks faster. By interacting with existing enterprise systems, Watson Orchestrate can complete to-do list items, like scheduling meetings and procuring approvals.
When McKinsey surveyed 1,500 executives across industries and regions in 2018, 66% said addressing skills gaps related to automation and digitization was a “top 10” priority. Forrester predicts 57% of business-to-business sales leaders will invest more heavily in tools with automation. That may be why Salesforce anticipates the addressable market for customer intelligence will grow to $13.4 billion by 2025, up from several billion today.
Users can interact with Watson Orchestrate using natural language — the software automatically selects and sequences prepackaged skills needed to perform a task, connecting with apps, tools, data, and history on the fly. For example, a sales director could ask Watson Orchestrate to monitor business opportunities, send an email alert when a deal progresses, and set up a meeting with the sales lead to discuss next steps.
Waston Orchestrate also understands and maintains context based on organizational knowledge and prior interactions. Concretely, this means it can act on information informed by a user’s preferences, like a preferred business application or email contact.
Watson Orchestrate follows acquisitions to expand IBM’s automation capabilities, including WDG Automation, Instana, MyInvenio, and Turbonomic, signaling the company’s ambitions in the enterprise automation space. According to IBM’s data, 80% of companies are already using automation software and tools — or plan to in the next 12 months.
Watson Orchestrate is currently available in preview as part of IBM’s Cloud Pak for Automation.
Cloud Pak for Data
IBM introduced Cloud Pak for Data three years ago as a way to help enterprises apply AI to data across hybrid cloud environments. Beginning this week, the service is gaining new AI-powered functionality, including AutoSQL, which automates the access, integration, and management of data without having to move it.
Managing data is highly complex and can be a real challenge for organizations. A recent MIT and Databricks survey of C-suite data, IT, and senior tech executives found that just 13% of organizations are delivering on their data strategy. The report concluded that machine learning’s business impact is largely limited by challenges in managing its end-to-end lifecycle.
AutoSQL uses the same query engine across sources, including data warehouses, data lakes, and streaming data. It’s part of an intelligent data fabric that leverages AI to orchestrate data management tasks — discovering, understanding, accessing, and protecting data across environments. The new fabric unifies disparate data into a unified view and aims to ensure data can be accessed without jeopardizing privacy, security, or compliance.
“Data quality and integration become major issues when pulling from multiple cloud environments,” IBM wrote in a blog post. “With the new data fabric and AI capabilities, [we’re] delivering what we expect to be a significant differentiator for customers by completely automating the data and AI lifecycle — the potential to free up time, money, and resources — and connect the right data to the right people at the right time, while conserving resources.”
Another part of the intelligent data fabric, AutoCatalog, taps AI to automate how data is discovered and maintain a real-time catalog of assets from across enterprises. Meanwhile, AutoPrivacy — another data fabric component — automates the identification, monitoring, and enforcement of policies on sensitive data across organizations.
The upgraded Cloud Pak for Data is available to customers starting today.
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