Webinar: 'Invisible Generative AI Risks: How IT Departments Should Control Them'
Check Point hosts a webinar on visualizing and controlling the 'invisible risks' of generative AI, such as confidential data leakage, by leveraging browser-based security alongside existing SASE environments.
📋 Article Processing Timeline
- 📰 Published: April 28, 2026 at 18:00
- 🔍 Collected: April 28, 2026 at 10:01
- 🤖 AI Analyzed: April 28, 2026 at 10:06 (4 min after Collected)
■ The Reality of Field-Led Generative AI Usage Outpacing Existing SASE
As the business application of generative AI expands rapidly, field-led adoption is leading the way in many companies. While tools like ChatGPT are easy to integrate into workflows, they are being used in ways unanticipated by traditional security designs, often exceeding the capabilities of existing SASE environments. With AI usage expected to grow further, IT departments are pressured to decide 'what to allow and how to control it.'
■ The Challenge of Unknown Input Content and Undetectable Information Leakage
A major issue in generative AI usage is the inability to track what information employees are inputting. Despite efficiency gains, the risk of unintentional input of confidential or personal information persists as an 'invisible' threat. Existing SASE provides limited visibility and control, often restricted to a binary 'allow or block' choice, which diverges from practical operations. Consequently, many IT departments continue operations without clear criteria for risk tolerance and control.
■ Practical Approaches to Visualize and Control AI Usage While Retaining Existing SASE
This seminar addresses these challenges by explaining how to visualize and control generative AI usage without significant changes to existing SASE environments. We will introduce methods using Check Point Browser Security to understand actual AI usage starting from the browser and apply flexible policy controls based on risk. Moving beyond the 'allow/deny' binary, we organize concepts for ensuring security without stopping AI usage, providing IT departments with the criteria needed for decision-making.
■ Recommended For:
- IT departments concerned about how to control expanding generative AI usage.
- Those facing challenges with undetectable information leakage risks due to unknown input content in ChatGPT.
- Those who feel current SASE is insufficient for visualizing and controlling AI usage.
- Those considering practical control methods without halting AI utilization.
- Those looking to achieve AI compatibility through additional measures without replacing SASE.
■ Organizers/Co-organizers
Check Point Software Technologies Ltd.
■ Cooperation
Open Source Utilization Institute Co., Ltd.
Majisemi Co., Ltd.
Majisemi will continue to hold webinars that are 'helpful to participants.' Public materials from past seminars and other current recruitment seminars can be found here.
Majisemi Co., Ltd.
3F Shiodome Building, 1-2-20 Kaigan, Minato-ku, Tokyo 105-0022
Contact: https://majisemi.com/service/contact/
As the business application of generative AI expands rapidly, field-led adoption is leading the way in many companies. While tools like ChatGPT are easy to integrate into workflows, they are being used in ways unanticipated by traditional security designs, often exceeding the capabilities of existing SASE environments. With AI usage expected to grow further, IT departments are pressured to decide 'what to allow and how to control it.'
■ The Challenge of Unknown Input Content and Undetectable Information Leakage
A major issue in generative AI usage is the inability to track what information employees are inputting. Despite efficiency gains, the risk of unintentional input of confidential or personal information persists as an 'invisible' threat. Existing SASE provides limited visibility and control, often restricted to a binary 'allow or block' choice, which diverges from practical operations. Consequently, many IT departments continue operations without clear criteria for risk tolerance and control.
■ Practical Approaches to Visualize and Control AI Usage While Retaining Existing SASE
This seminar addresses these challenges by explaining how to visualize and control generative AI usage without significant changes to existing SASE environments. We will introduce methods using Check Point Browser Security to understand actual AI usage starting from the browser and apply flexible policy controls based on risk. Moving beyond the 'allow/deny' binary, we organize concepts for ensuring security without stopping AI usage, providing IT departments with the criteria needed for decision-making.
■ Recommended For:
- IT departments concerned about how to control expanding generative AI usage.
- Those facing challenges with undetectable information leakage risks due to unknown input content in ChatGPT.
- Those who feel current SASE is insufficient for visualizing and controlling AI usage.
- Those considering practical control methods without halting AI utilization.
- Those looking to achieve AI compatibility through additional measures without replacing SASE.
■ Organizers/Co-organizers
Check Point Software Technologies Ltd.
■ Cooperation
Open Source Utilization Institute Co., Ltd.
Majisemi Co., Ltd.
Majisemi will continue to hold webinars that are 'helpful to participants.' Public materials from past seminars and other current recruitment seminars can be found here.
Majisemi Co., Ltd.
3F Shiodome Building, 1-2-20 Kaigan, Minato-ku, Tokyo 105-0022
Contact: https://majisemi.com/service/contact/