AI, Supply Chain Are Fertile Areas for Cybersecurity Investment

The past year has been a busy one for startups, with investors reevaluating their rules on what kind of companies to invest in and larger companies going shopping for innovative technologies. However, focusing on individual acquisitions or startup launches makes it easy to miss the investment trends.

Recent announcements from MACH37, an accelerator focused on innovation in cybersecurity, and DataTribe, a venture capital firm focused on cybersecurity startups, provide a glimpse of the areas in which investors are most interested in spending their money and time.

Though Mach37 and DataTribe had different approaches in how they identified innovation in cybersecurity, they are both looking for companies and technologies capable of solving increasingly complex cybersecurity challenges. Right now a lot of love is being showered on anything with artificial intelligence (AI) in the tag, but it will take time before we know how those investments will play out.

Mach37 Plants the Seeds

Mach37 focuses on scaling and market integration because the goal is building up each startup's potential for long-term growth.

Accelerators are a complex pressure test for fledgling companies. Many potential investors, early-adopter customers, and potential channel partners want to see how companies perform throughout an accelerator program before investing or partnering. Startups benefit from mentorship opportunities, learn to develop sustainable business practices, and get help lining up customers.

Mach37 named a range of startups offering AI-powered software-as-a-service (SaaS) platforms, intelligence-grade cloaking, and cybersecurity intelligence platforms to its cyber accelerator class of 2023 (its 16th cohort).

DataTribe Grows the Seeds

In contrast, DataTribe zeroes in on the seed stage, seeking more fundamental, ground-breaking shifts in cybersecurity and data science.

The venture capital firm recently announced the DataTribe Challenge, where seed-stage cybersecurity startups applied for the opportunity to win up to $2 million in seed capital. The finalists were selected based on how they tackled such areas as secure logins and AI risk management. The five finalists focused on hardware bills of materials and vulnerability analysis (Ceritas), secure login and authentication (Dapple Security), software bills of materials and supply chain security (Vigilant Ops), serverless SecOps (LeakSignal), and scoring AI/machine learning (ML) models as part of risk management (Ampsight).

The winner of the DataTribe Challenge was Vigilant Ops, which signals an increased focus on securing the building blocks of hardware and software products, says John Funge, managing director at DataTribe.

"Companies that are leveraging the value of new data sets to include hardware and software bill of materials [HBOMs and SBOMs] are seizing an over-the-horizon opportunity to meet the challenges posed by an increased focus on software and hardware supply chain security," Funge says.

Investors Eat Up AI/ML

While AI might feel new, it has actually been a critical factor in cybersecurity for years. The development and evolution of artificial intelligence has shaped the direction of cybersecurity, in terms of technical capabilities and the democratization of tool development and use. The defensive use of AI will need to evolve not just to answer the onslaught of new threats, but also to provide a new level of continuous monitoring, anticipate and predict where threats will go next, look for poisoned data meant to throw off AI models, detect false positives, and characterize other new phenomena.

The focus on authentication, threat intelligence, and AI tools across these two programs reflects the broader cybersecurity landscape, where organizations are looking for better authentication methods and improved intelligence about attacker activity. Supply chain security is also becoming a bigger part of the conversation as adversaries increasingly target third-party components in order to compromise applications and devices.

Back in 2021, almost 75% of enterprises planned to spend their IT budget on AI and ML. Now it's close to 100%. Organizations have witnessed the power of AI for threat, defense, and operational progress, and now they are looking to buy.

Here the startup space often outpaces large enterprise solutions in speed of innovation and product availability. That makes it an exciting time for cybersecurity startups focusing on AI, as well as investors looking for new ways to tackle old problems.