What is AI, Actually?

Artificial Intelligence (AI) has become quite a buzzword nowadays. Whether it’s from customers, LinkedIn conversations, or culture, we’re sure you’ve felt the pressure to implement it! However, it’s especially important for IT providers to critically evaluate whether it’s indeed the universal solution that it’s portrayed as. IT and cybersecurity providers must consider not only the effectiveness of AI but also its relevance to your specific business needs. Is AI genuinely the best tool for the job, or are there other technologies and strategies that could better serve your unique requirements?

Artificial Intelligence (AI), where machines are taught how to make decisions and categorize patterns based on inputs and available data, has been around since the mid-20th century. Since then, it has become the driving force behind many traditional security solutions, such as antivirus (AV) and endpoint detection and response (EDR). Through AI, AV and EDR can recognize patterns, identify suspicious behavior, detect irregularities, and more, based on whether the activity is labeled good or bad, familiar or strange. 

Generative AI, on the other hand, was invented in the mid-2010’s in response to the desire to efficiently harness the vast amount of data available nowadays. This form of AI generates information for the user in natural language, such as ChatGPT. Businesses, regardless of industry, are still navigating the best ways to use generative AI for their organization. Jack Rasmus-Vorrath, Head of AI at Blackpoint, emphasized the importance of applying these technologies judiciously. He advocates for their use only in contexts where they provide the most utility and have the strongest impact. 

While AI performs tasks that would otherwise require human intelligence, automation refers to the use of technology to perform tasks or processes automatically, without human intervention. These tasks are well-defined, repetitive, and based on pre-set rules.  Additionally, unlike AI, automation does not use machine learning to enhance and refine its capabilities over time. 

Two examples of automation can be found within Blackpoint’s offering. Ransomware Response, a feature of our Managed Detection and Response (MDR) service, automatically stops all types of ransomware deployments, including drive-by attacks that occur within seconds. Additionally, Managed Application Control, a product within the Blackpoint Response suite, automatically stops unapproved software from running within a network. Within SNAP-Defense, these solutions act without initial review by a Security Operations Center (SOC) analyst. By intentionally and deliberately using automation in these services, Blackpoint is able to target significant cyberthreats with precision, preventing the exploitation of trusted software and the deployment of ransomware.  

While AI is good at recognizing patterns in data, deciding what to do with those patterns becomes challenging when threat actors use advanced tactics that blend into routine behavior. Taken out of context, good and bad behavior can look exactly the same. Hackers frequently use the same tools that administrators use and steal identities to hide their malicious activity in a background of benign noise. They exploit software that’s native to a company’s network through known vulnerabilities, publicized proof-of-concepts, or free trials. Therefore, detection capabilities that go beyond malware are critical to staying one step ahead of threat actors.  

Today, Blackpoint Cyber pairs its cutting-edge technology and real-world experience with live, human-led response. Our thoughtful utilization of automation, as Jack stated, as well as our hyper focus on response and remediation, enables us to achieve the industry’s fastest response and highest efficacy. The result? The industry’s Active Cybersecurity leader protecting your six.  

Ready to learn more about the Blackpoint way? Schedule a meeting here.