In the past year, Generative AI (GenAI) availability for businesses has swept the market, offering significant boosts in productivity. To successfully seize this opportunity, however, businesses will need to ensure they invest in the right solutions.

Faced with options like commercial AI services and customizable open-source Large Language Models (LLMs), business leaders must navigate a complex landscape of risks and benefits. This choice, influenced by factors like speed to market and data security, is crucial for companies looking to strategically invest in GenAI.

With the rapid proliferation of Generative AI (GenAI), developers are increasingly integrating tools like ChatGPT, Copilot, Bard, and Claude into their workflows. According to OpenAI, over 80 percent of Fortune 500 companies are already using GenAI tools to some extent, whilst a separate report shows that 83 percent of developers are using AI-tools to speed up coding.

However, this enthusiasm for GenAI needs to be balanced with a note of caution as it also brings a wave of security challenges that are easily overlooked. For many organizations, the rapid adoption of these tools has outpaced the enterprise's understanding of their inherent security vulnerabilities. This would yield a set of blocking policies for example, Italy had at one point this year completely blocked usage of GPT, which is never the answer.

This misalignment could not only compromise an organization’s data integrity but also impact its overall cyber resilience. So, how should AppSec teams, developers, and business leaders respond to the security challenges that accompany the widespread use of GenAI?