What VCs are looking for in the next wave of cybersecurity startups

In cybersecurity, AI often stands for “already implemented.” Security vendors have used AI-based technologies to use existing knowledge databases and address talent gaps. As an investor who focuses on backing expansion stage B2B enterprise startups in cybersecurity, AI, and DevOps, with recent investments in cybersecurity company Huntress and AI startup Weights & Biases, I feel fortunate to have a unique vantage point on both AI and cybersecurity companies set to take off in 2024 and beyond.

From my perspective, today’s organizations face an uphill battle when protecting their data and networks. Cyber threats are becoming more frequent and severe as potential attack surfaces multiply and hackers orchestrate increasingly sophisticated schemes. Bad actors are becoming more efficient thanks to the power of artificial intelligence (AI), perpetrating more personalized attacks and reaching a larger scale, resulting in billions of dollars in business losses.

Meanwhile, organizations of all sizes are innovating new defenses with incredible speed, often also tapping the capabilities of advanced AI. Companies are eager for solutions that enable them to step up their game. According to Gartner, global enterprise security spending will reach an estimated $188 billion this year and grow to $215 billion by 2024. Security software spending is the least likely area of IT to be cut in an economic downturn, according to Morgan Stanley.

In the coming year, they’ll seek to partner with players, enabling cybersecurity teams to enhance productivity and address talent shortages while staying on top of mounting threats.

What VCs are looking for in the next wave of cybersecurity startups

The advent of large language models (LLMs), such as ChatGPT, has brought new opportunities for AI-driven innovation within the industry. Here are some features investors will be looking for in the next crop of successful cybersecurity startups:

A proactive approach to customer education

During the cloud computing revolution, many enterprises rushed to implement cloud solutions with security as an afterthought. This resulted in some cybersecurity catch-up. So far, the inverse has been true for generative AI (GenAI). While companies are eager to reap the benefits of the technology, they are hyper-aware of the risks of exposing sensitive information or breaching customers’ trust. Concerns have grown amid high-profile data leaks at companies like Samsung. In response, many companies have been gun-shy about launching GenAI initiatives, limiting usage to a small cohort or sometimes issuing blanket bans.