Intellyx BrainBlog by Jason English for Tines
As my colleague Eric Newcomer mentioned in the previous chapter of this series, GenAI changes the security automation game, with multi-system discovery, documentation, and task execution capabilities that can reduce cognitive load and toil for security analysts.
To get started, all the analyst has to do is ask an AI-powered solution like Tines Workbench to pull in data and investigate their authorized systems using a natural language chat interface, with intuitive summaries to keep up awareness of an ever-changing application tech stack.
But conversational interfaces like chatbots are only the first step on the road toward the productivity that AI can help deliver for the SOC.
To get sustainable improvements, we must go beyond simply chatting with an LLM.
We need to combine the learnings and patterns from a broader set of development, operations and business stakeholders, with automated workflows that include machine language-driven skillsets and AI-driven tasks.
Learning automation lessons from RPA
Starting about a decade ago, we saw the fast rise of RPA (robotic process automation), through companies like UiPath and Automation Anywhere alongside newer workflow automation tools fostered within industry giants such as Salesforce and Microsoft.
We expected RPA to recruit a bonafide workforce of semi-autonomous bots to help us out. Literally, a ‘bot for every employee’ to do our bidding, capturing and replaying our process of logging into different SaaS tools, clicking buttons, entering strings into fields, and automating the next logical step in a workflow…
Read the full BrainBlog on Tines.com here: https://www.tines.com/blog/put-ai-to-work/
