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How many emails did you receive today? How many of those emails were marketing messages from a company trying to get you to request more information, buy something, or buy more? Most of the emails you receive daily are part of an overall marketing plan since most companies see a massive ROI on their email outreach efforts.

Should generative AI systems have access to your establishment’s sensitive data? Many people seem to think so. This burgeoning new technology streamlines many tasks and makes operations cheaper, but it is important

If there’s one thing you can always count on in the realm of cybersecurity, it's that things are always changing. One area where the power of AI is on full display is cybersecurity. The intersection of AI and cybersecurity is unique, as both security professionals and cybercriminals view it as a powerful tool. In short, AI can launch sophisticated attacks and thwart them via complex machine learning algorithms that recognize and respond to threats in real-time. There’s no question that AI is at the forefront of current cybersecurity trends, given that a Forbes report revealed that most businesses prioritize machine learning and AI in their security budgets. But what do these rapid industry shifts mean for cybersecurity frameworks and the day-to-day management of network and data protection? How AI Is Changing Approaches to Cybersecurity As cybercriminals become more sophisticated and networks expand, staying one step ahead of trouble is becoming increasingly difficult for security teams. With so many threats coming from every direction, it can be easy to miss indications of compromise, fail to detect intrusions or respond to incidents. Combining AI and cybersecurity can make it easier to address security threats more quickly. Consider some of these capabilities: Machine learning algorithms allow rapid data analysis to reveal anomalies and threats more quickly. You can automate repetitive tasks, like reviewing logs and alerts, so that human analysts can focus on more strategic priorities. Companies can utilize predictive analytics to use historical data to predict potential attack vectors and simulate attack scenarios to develop and refine responses. Security automation autonomously detects and stops threats to prevent breaches. Two Concerns About AI and Cybersecurity While AI and cybersecurity are inextricably intertwined, businesses must recognize that developing and implementing these tools requires an intense focus on their safety to ensure they don’t worsen risks — or create new ones. Without this attention, it’s possible to implement AI solutions that contain vulnerabilities for cybercriminals to exploit. Two of the biggest concerns regarding securing AI are data protection and control. AI tools must prioritize data protection and security and avoid errors that could expose sensitive data to bad actors. If the AI tool has mistakes or weaknesses that are easy to work around, both human users and corporate systems could be at risk for exposure. The second issue involves AI’s security automation capabilities. If the AI tool falls into the wrong hands, the consequences could be devastating, so protocols must be in place to halt its capabilities and prevent data manipulation, a cyberattack, or other harmful outcomes. There’s no doubt that the future of the digital revolution relies heavily on AI and cybersecurity. Despite rapid industry shifts and widespread adoption, there’s still a long way to go to find the best ways to embrace the technology for a safe and secure digital future. Used with permission from Article Aggregator

Could cyberattacks wipe out your establishment in minutes? Many small and medium-sized businesses (SMBs) think it won’t happen to them until it’s too late. Keep reading to learn more. An Escalating Issue

The inventory management process includes having a team member count all materials and finished goods available in your storage center or backroom so they can decide which products are in high demand