Cisco says that by the end of the year a generative AI-based policy assistant will be able to interact with network admins to help them optimize policy management. Security and IT administrators will be able to describe granular security policies for tasks like firewall management, and the assistant will evaluate how to best implement policies across the security infrastructure.
Juniper
Juniper is integrating ChatGPT with its Marvis virtual network assistant. Marvis, driven by the AI technology Juniper got with its acquisition of Mist Systems, can detect and describe network problems in natural language. By adding ChatGPT capabilities, Juniper is expanding the role of Marvis, augmenting its documentation and support options to help IT administrators.
Vendors collaborate to provide on-prem generative AI.
Dell Technologies and Nvidia have launched an initiative called Project Helix to help enterprises build and manage generative AI models on-premises. The goal is to support the complete generative AI lifecycle including infrastructure provisioning, modeling, training, fine-tuning, application development, and deployment. Dell will contribute its PowerEdge servers, Nvidia will provide the GPUs, networking and software suite, which includes its NeMo large language model framework and NeMo Guardrails software for building secure chatbots.
And as the generative AI vendor ecosystems grows, we will undoubtedly see more collaborations like the one recently announced between Nvidia and ServiceNow in which the companies work together to build applications for specific business processes and workflows. ServiceNow says the first results of the collaboration will be aimed at building generative AI applications for enterprise IT departments, including trouble-ticket summarization, auto-routing and auto-resolution; incident severity prediction, intent detection, semantic search, and root cause analysis.
In addition, we can expect that the hyperscalers, as well as a new generation of SaaS startups, will be delivering vertical-specific generative AI applications. For example, Google has launched a suite of generative AI-based tools for medical imaging. And Gartner predicts that in two years, “more than 30% of new drugs and materials will be systematically discovered using generative AI techniques, up from zero today.”
McKinsey says, “CEOs should consider exploration of generative AI a must, not a maybe. Generative AI can create value in a wide range of use cases. The economics and technical requirements to start are not prohibitive, while the downside of inaction could be quickly falling behind competitors.”
What enterprise IT leaders should be doing now.
Set policies
According to Gartner, “Your workforce is likely already using generative AI, either on an experimental basis or to support their job-related tasks.” To avoid “shadow” usage, Gartner recommends crafting a usage policy rather than enacting an outright ban. The policy should simply state: Don’t input any personally identifiable information, sensitive information, or intellectual property.
And the company should put monitoring tools in place. The vendor community is already stepping up, with companies like Zscaler, ExtraHop, and LayerX offering ways to monitor and control employee usage of ChatGPT.
Set guardrails.
Forrester analyst Mike Gualtieri says organizations need to set policies that enable developers to experiment with generative AI, but to establish guardrails, such as requiring that the code go through a security scanning tool, and having a human double-check it. If something goes wrong, “You can never blame GPT; it’s your responsibility,” cautions Gualtieri.
Educate and train.
The buzz around ChatGPT has generated excitement but also some fear associated with practical concerns like cybersecurity attacks generated by these systems, as well as more emotional worries that machines are coming to replace us.
We posed that very question to ChatGPT and got this: “My purpose is to assist and augment human capabilities, rather than replace them. While AI technologies like ChatGPT can automate certain tasks and provide support, they are not designed to replace the expertise and decision-making abilities of IT professionals.”
It’s important for enterprise IT leaders to educate employees across the company on the potential for Generative AI to make their lives easier. It’s also important to launch training programs for IT staffers.
Beef up security.
McGillicuddy predicts that “malicious actors will be the most prolific users of generative AI for the next year or so.” The concern is that generative AI will be able to write convincing phishing emails and help hackers create deep fakes. Enterprise security leaders need to up their game when it comes to anti-phishing defenses and security tools like data-leak protection.
Create interdisciplinary teams.
IT exists to support the business, so IT leaders need to create cross-functional teams that can identify and prioritize business processes that can benefit from generative AI.
Develop a long-range strategy.
Enterprise IT leaders need to develop an organization-wide generative AI strategy that answers several fundamental questions. How can it help cut costs? How can it make employees more productive? How can it create new business opportunities? What’s the best way for us to acquire it? How can we implement it in a way that avoids the pitfalls?