Recently at Omnissa ONE, we announced Omni, our upcoming artificial intelligence assistant. As part of that announcement, our SVP of Product Bharath Rangarajan first shared the four-part trust model that outlines the AI plans on which we are executing. Today, I want to share this model with this wider audience and dig a bit deeper.
Given the huge volume of data that exists in any end-user computing environment, analytics, machine learning, and artificial intelligence are essential for making sense of all the information. This was true long before the current wave of generative AI development, and we have been leading the way for quite a while now, starting with Omnissa Intelligence (recently renamed to reflect its importance in the Omnissa Platform), which debuted in 2018.
However, the recent advances in GenAI provide opportunities that every organization and technology provider are looking to employ. At Omnissa, we are taking a systematic and incremental approach to expanding our data science capabilities to include both predictive and GenAI, while driving toward our vision of an autonomous workspace. We want to ensure that each step along this journey solves relevant problems and delivers tangible value to our customers. And we will do this in a responsible way, not only in terms of security and privacy but also in terms of cost.
Our AI strategy can be described by a four-part model, with stages we refer to as Alert, Assist, and Advise culminating in our final vision, the autonomous workspace.
At the first level, predictive AI can be used to find actionable insights within data and discover correlating events. This goes way beyond what may have been possible with manually setting up alerts and digging through data. This work is about helping customers find what may have been previously unknown — such as hidden anomalies and correlating factors that point to changes in the environment, whether they are performance issues to be resolved or general trends to note.
Omnissa already provides these capabilities today with our Insights and Guided Root Cause Analysis features, available in Omnissa Intelligence. We often give the example of using Insights to discover increasing rates of app and OS crashes, and Guided RCA to correlate the crashes to specific hardware models and software, OS, or firmware updates. But consider the thousands of metrics that are collected by Intelligence, as well as other data that may be incorporated, and how these capabilities can support organizational goals of a proactive, shift-left mindset. These Alerts call IT to action and direct them to resolve issues.
GenAI and LLMs have emerged in the last few years as a revolutionary way to interact with data in a conversational way. This has democratized access to data, and actionable information within that data. The requirements to understand SQL and data structures or have custom reports built are eliminated and replaced with natural language questions and conversations. Given the nature of data in end-user computing environments — including detailed product documentation and massive amounts of telemetry data — there is a clear opportunity to use AI to interact with this data using natural language. At Omnissa ONE, we announced our AI assistant, Omni, will do just that.
In the beta of Omni, coming in early 2025, customers will be able to use knowledge search capabilities to get help and tips directly in the Omnissa consoles. This knowledge will be based on our product documentation, KBs, and other technical resources.
The other key domain coming in the Omni beta is data search, which will help admins analyze the vast variety of metrics available in Omnissa Intelligence. Customers we have spoken to are excited for the potential time savings in building out queries. Instead of building or finding a dashboard one at a time, imagine being able to ask as many questions as you want as they occur to you. For example, you could ask “How many BYOD iPhones have enrolled in the last 90 days?” Or, after observing an issue in one machine, you could ask how many machines have a similar issue. We anticipate that this capability will make data more accessible to broader stakeholders (e.g., Management, Security, Finance, Procurement, Legal, LoB) to accelerate and improve decision making. This will enable EUC admins to focus on high-value work, rather than being the gatekeepers and report creators for the rest of the business.
Because Omni is being built on the Omnissa cloud service platform, customers will also be able to ask any question related to the documentation or data domains described above in the Omni interface, which will be present across the UEM, Horizon, Intelligence, and Omnissa Connect consoles.
Omni will continue to expand its capabilities in the future, providing a conversational interface for many of the capabilities throughout the Omnissa Platform, such as Omnissa Freestyle Orchestrator. Today, Freestyle Orchestrator provides a powerful orchestration framework to automate workflows across our customers’ deployments. These orchestrations serve as a customer-defined agent, automating the steps and decisions in common workflows. In the future, Omni could provide a natural language interface for these automations, going beyond the self-service capabilities exposed recently with Quick Actions.
Looking into our future roadmap, the next step in our AI trust model is to proactively provide recommendations for remediating issues or optimizing environments, based on best practices and conditions observed in the environment.
In other words, instead of waiting for administrators to ask questions, Omni will act as an advisor, proactively calling attention to issues or optimization opportunities, with specific remediation recommendations. Imagine Omni providing information such as, “A new CVE is impacting 350 devices in your environment. Do you want to deploy the patch?” The administrator could then choose to take the action.
These proactive recommendations will not only recommend an improvement but also provide the one-click automation for the Omnissa Platform to implement the recommendation, remediate the problem, or optimize the deployment. Once customers gain confidence in these recommendations, they can ask Omnissa to take enact this recommendation automatically next time, turning the proactive alert into an intelligent agent, and realizing the self-configuring, self-healing, and self-securing Autonomous Workspace vision.
As we have expressed many times before, our ultimate vision is that of an Autonomous Workspace, which can be self-configuring, self-healing, and self-securing. In the AI model that we are describing, this would mean that when an issue or opportunity for optimization is observed, the system could potentially take action — again based on best practices and considerations related to the specific environment — on its own without any human involvement.
Naturally, a large amount of trust must be established between the AI models and IT teams. IT teams must be able to take a gradual approach, keeping a human in the loop or on the loop for as long as they desire. Then they may start allowing autonomous actions on low-stakes tasks, with a very limited scope.
However, you can see the potential. Imagine the assistant saying, “Blast optimizer settings were adjusted for 50 users based on detected usage patterns and network conditions.” And. of course, the admin should be able to see exactly what was done and be able to revert or modify if necessary.
Omnissa AI trust model
We are in the early stages of this AI trust model. Given the critical nature of EUC, taking a measured, privacy- and security-centric approach is the fundamental principle of our strategy, as it has always been with all our products. (You can learn more in the Omnissa Trust Center.) We will keep IT informed and in control, providing full transparency and letting them decide what they are comfortable automating.
We are excited about the future possibilities and hope you are, too. One way you can get ready is to make full use of the data capabilities in Omnissa Intelligence. We are continuously adding new options for telemetry, spanning desktop and mobile devices, experience data, virtual desktops, third-party integrations, and much more.
We are eager to speak with you, our customers, about your desires, concerns, and questions. Omnissa ONE was a wonderful opportunity to bring together and meet many customers at once. I look forward to all the continuing conversations in 2025 and beyond.
此内容由惯性聚合(RSS阅读器)自动聚合整理，仅供阅读参考。 原文来自 — 版权归原作者所有。