Attack surfaces are expanding with cloud adoption and other digital transformation initiatives. As a result, the ability to rapidly identify and address vulnerabilities is paramount. Enter AI chat, which is reshaping the security landscape.
AI chat can produce customer-specific, real-time, fresh data. This eliminates the need for exhaustive retraining with every dataset change. Customers get remediation advice unique to their environment while MSPs glean the satisfaction of their customers.
MSPs are missing out by not using AI chat to automate their data extraction processes to elevate customer service. But understanding how to capitalize on AI chat is equally imperative.
Transformation of the Landscape
The security landscape has evolved significantly since the Covid-19 pandemic. Remote work and scattered employees have increased attack surfaces. This has made it critical to consider the impact of the tools your organization uses.
Boaz Gorodissky
Notably, it’s important to determine whether those tools support or hinder how employees deliver services to your customers. Being able to automate a portion of an employee’s manual labor can drastically improve their as well as the customer’s experience.
AI chat empowers MSPs to achieve this by automating tedious manual processes and analyses. Cybersecurity teams can then focus on more strategic priorities knowing that their AI assistant is continually scanning for risks and generating remediation playbooks customized to each client environment.
Robust automation also enables proactive security posture improvements. Rather than waiting for threats to emerge, MSPs can proactively model hypothetical attack scenarios and evaluate their clients’ resilience using AI chat. Any gaps identified can be swiftly remediated to reduce attack surfaces before they are exploited.
Most organizations have myriad data waiting to be used. Without AI, MSPs are getting a fraction of the system’s value. AI chat seamlessly extracts the data for MSPs to serve their customers. According to a study, 68% of data available to businesses is left quiescent and underutilized. This means most MSPs miss the opportunity to leverage valuable insights, drive innovation, and better serve their customers.
Capitalizing on AI Chat
AI chatbots offer the appealing promise of simply asking questions and receiving answers. However, many current AI tools operate at a considerably basic level, merely regurgitating public information from sources like Google.
To truly capitalize on AI’s potential, MSPs must move beyond these rudimentary “open AI wrappers,” and adopt more advanced capabilities like retrieval-augmented generation (RAG). RAG models allow AI systems to access and synthesize proprietary customer data, internal databases, and other nonpublic information sources that generic models lack.
Adopting AI chat capabilities requires MSPs to exercise caution regarding the accuracy and relevance of outputs. Blindly trusting AI-generated responses risks providing nonsensical or inappropriate recommendations.
MSPs must understand the limitations of their AI systems, ask the right types of queries that align with the data available, and implement robust processes for validating outputs against known scenarios and subject matter experts. Continuously testing and refining the AI models is essential.
To ensure that AI chat recommendations are accurate, effective, and tailored to each customer, technical experts within MSP organizations can ask the chatbot questions to test its validity. Since the AI is translating natural language to a specific database language, it’s important to be suspicious in the beginning. A best practice is to take regular samplings, decide how logical the output is, and ultimately slowly build trust with the chatbot.
AI Chat Is a Force Multiplier
Overall, by integrating AI support, MSPs can deliver enhanced real-time cybersecurity value. In addition, it can help build stronger trust with clients through transparency and cultivate an internal culture of security excellence.
Ultimately, AI chat serves as a force multiplier, helping MSPs comprehensively fortify their customers’ security postures while optimizing their own operations.
Boaz Gorodissky is chief technology officer of XM Cyber, where he oversees all technology and product development. His responsibilities include identifying customer needs and working with product management to define detailed requirements and a technology roadmap aligned to the XM Cyber vision.
Featured image: iStock
