The rapid expansion of artificial intelligence is often associated with new technological risks, but a recent Goldman Sachs analysis presents a different perspective. Rather than disrupting the cybersecurity industry, AI is expected to become one of its strongest long-term growth drivers. As enterprises continue investing heavily in AI infrastructure, Wall Street anticipates a second wave of spending focused on securing these increasingly complex systems.

While 2025 is expected to be a defining year for enterprise AI adoption, Goldman Sachs believes the largest acceleration in cybersecurity spending will emerge between late 2026 and the first half of 2027. This delayed investment cycle reflects how businesses typically prioritize deploying new technologies before allocating substantial budgets to address the security challenges that accompany them.

From Cloud Computing to AI: A Familiar Investment Cycle

Goldman Sachs compares the AI adoption cycle with the evolution of cloud computing over the past decade. Historically, dedicated cloud security spending remained minimal during the early years of cloud adoption before expanding into a meaningful percentage of overall cloud budgets as organizations recognized new vulnerabilities.

Analysts expect a similar pattern with artificial intelligence. Companies are initially investing to improve productivity, automate workflows, and strengthen competitive positioning. Only after AI systems become deeply integrated into business operations are organizations expected to significantly increase spending on specialized cybersecurity solutions.

According to Goldman Sachs, this delayed adoption curve could add approximately two to three percentage points to annual cybersecurity industry growth rates through 2028 as AI-related security budgets expand.

Scale Creates a Competitive Advantage for Industry Leaders

Rather than expecting startups to dominate the AI security market, Goldman Sachs argues that established cybersecurity companies hold meaningful competitive advantages. Modern cybersecurity depends heavily on machine learning models trained using vast quantities of real-world security data, much of which has been accumulated over many years.

Leading cybersecurity firms possess extensive proprietary databases, sophisticated detection algorithms, and continuous feedback from human security professionals. These assets create significant barriers to entry for newer competitors, even those developing advanced AI technologies.

In addition, many established companies maintain strong balance sheets that enable them to acquire innovative private firms, allowing them to integrate emerging technologies while reinforcing their existing market positions.

Palo Alto Networks, CrowdStrike, and Okta Stand Out

Goldman Sachs identifies several publicly traded cybersecurity companies as potential long-term beneficiaries of expanding AI security budgets. Palo Alto Networks, CrowdStrike, and Okta are expected to strengthen their competitive positions as enterprises seek increasingly sophisticated security platforms.

Each company already plays an important role in protecting enterprise computing environments. As artificial intelligence expands the complexity of corporate IT infrastructure, demand for advanced threat detection, endpoint protection, and identity management solutions is expected to grow alongside overall AI adoption.

Among the three companies, Goldman Sachs highlights Okta as offering the greatest upside potential, largely because of its specialization in identity and access management—an area expected to become increasingly critical as AI systems require stronger authentication and access controls.

Looking Ahead

The continued expansion of artificial intelligence is reshaping not only how businesses operate but also how they approach cybersecurity investment. Goldman Sachs believes the current moderation in enterprise cybersecurity spending should be viewed as a temporary phase before a much larger wave of AI-related security investment materializes.

For investors, the key challenge will be identifying which cybersecurity providers can best convert their technological expertise, proprietary data, and scale advantages into sustainable earnings growth as AI security budgets accelerate. The companies that successfully capitalize on this structural shift may be well positioned to benefit from one of the cybersecurity industry’s most significant growth cycles in the years ahead.