Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

The rush to work faster with artificial intelligence (AI) risks encouraging employees to accidentally put sensitive data at risk. Take this scenario: someone in the procurement team has a tight deadline, so they upload a confidential contract into an AI tool to review a few redlines. It’s unclear if the AI system is storing the data from the contract, how long it’ll be retained, and if the data will resurface in a future prompt to someone else.

Departing workers can pose significant risks to data. Let me share a story about an individual who stole and deleted valuable research data right before submitting his resignation: six weeks after a contingent worker left the company, the FBI contacted us. It turned out that the individual had tried to sell the company’s confidential data to a third party. When he left, everything seemed normal.

Every year, companies reevaluate their budgets, making tough calls on where to invest for the most impact. In many organizations, cybersecurity spending is often seen as a cost center. However, without adequate security investments, companies put themselves at greater risk for data breaches that could disrupt business operations and damage customer trust, ultimately costing the company a lot more in the end.

Cloud adoption among enterprises accelerated around 10 years ago. During this time, network-based tools emerged as solutions that could protect data as it traveled to the cloud. These solutions, including Security Service Edge (SSE) and Cloud Access Security Brokers (CASB), utilized network-based proxy architectures that could intercept and control traffic.

We are in the midst of a major technological shift. And when shifts happen, new industry-defining companies emerge. The winners aren’t just those with great ideas—they are the ones who adapt and respond to change the fastest.