Palo Alto Networks CEO: Enterprises trail consumers in AI adoption

Enterprises trail consumers in AI adoption, a significant gap highlighted by Palo Alto Networks' CEO, who warns of a multi-year catch-up cycle. This corporate lag is driven by major security and governance challenges, prompting firms like Accenture to mandate AI use and others to accelerate hiring for security roles.

AI Insiders Weekly: Top Stories from February 16-22, 2026 - Enterprise Uptake Falls Behind

Enterprises are adopting AI more slowly than consumers due to significant security, governance, and visibility hurdles. Unlike consumer apps, corporate AI requires robust control over data traffic and a consolidated security framework, creating a cautious, multi-year rollout cycle similar to early cloud adoption.

Palo Alto Networks CEO Nikesh Arora stated on the company's Q2 2026 earnings call that consumer generative AI adoption is "far outstripping enterprise." He identified coding assistants as the only current, large-scale business use case. Arora noted that while some clients process "millions of tokens," the primary obstacle is consolidating AI traffic for security governance. Comparing the current lag to the slow initial shift to cloud computing, he projected a two-to-three-year catch-up period for enterprise AI. Despite this, strong demand for security platforms drove Palo Alto's 15 percent year-over-year revenue growth to $2.6 billion.

Accenture Turns Promotions Into an AI Usage Scorecard

Accenture is now enforcing AI adoption by linking it to career advancement. According to an internal memo detailed in Morning Brew's report, senior managers risk their promotion prospects if they do not regularly use internal AI tools like AI Refinery and SynOps. This usage data is now a factor in leadership reviews for most of the firm's 780,000 employees, with some exceptions for federal contracts and certain European countries. The mandate follows the company's training of 550,000 workers in generative AI and aims to make Accenture the "most AI-enabled workplace."

Security Hiring Rises as AI Increases Both Threats and Productivity

As enterprises slowly move toward AI, their security teams are already adapting. The World Economic Forum's Global Cybersecurity Outlook 2026 found that 77% of organizations use AI for security tasks like phishing detection and anomaly response. While automation helps manage alerts, a 4.8-million-person cyber skills gap persists. Consequently, hiring now focuses on professionals skilled in AI governance, model tuning, and auditing LLM output. Common tasks AI now handles include:

• Correlating low-level alerts across logs
• Triaging probable false positives
• Flagging risky user behavior in near real time

This growing reliance on AI for security is expanding the market for vendors, which research firm Cybersecurity Ventures pegs at roughly two trillion dollars by 2026. Ultimately, the focus on visibility, talent, and governance shows that businesses are building the foundational security and policy layers necessary for widespread, production-grade enterprise AI.

---

How far behind are enterprises compared with consumers in AI adoption?

Palo Alto Networks CEO Nikesh Arora told investors in February 2026 that enterprise AI adoption trails consumer use by "at least a couple of years."
On the earnings call he could name only one mass-scale enterprise use case: coding assistants. By contrast, consumers already lean on AI daily for search, shopping, creative tools and customer support.

Why is enterprise uptake moving so slowly?

Arora points to three friction points:

1. Traffic sprawl - firms run "millions of tokens" through separate LLM endpoints, making visibility and policy control hard.
2. Missing guardrails - AI needs "a different set of controls and tools" that most security stacks still lack.
3. Wait-and-see mindset - enterprises took 2-3 years to move apps to cloud and appear to be on a similar cautious path with AI.

Until these gaps close, coding assistants remain the only AI workload generating meaningful traffic inside large companies.

How is Accenture pushing its workforce to catch up?

Beginning with the 2026 promotion cycle, associate directors and senior managers must show weekly log-ins to Accenture AI platforms (Refinery, SynOps, etc.) or risk being passed over for leadership roles.
The firm already trained 550 000 employees in generative AI during 2025; now "use of our key tools will be a visible input to talent discussions."
Limited exclusions apply - staff in 12 EU countries and on certain U.S. federal contracts are exempt - but the message is company-wide: no AI usage, no advancement.

Is limited enterprise AI hurting cybersecurity vendors?

Yes - but only in the short term. Arora admits coding assistants "don't generate a lot of network traffic," crimping the data pipeline his products protect.
Still, Palo Alto posted 15 % YoY revenue growth to $2.6 billion in Q2 2026 as companies race to build AI-security "arms races" today, betting that broader AI workloads (and the traffic they bring) will follow once governance matures.

What new roles is AI creating in cybersecurity?

The 4.8 million-person cyber skills gap is pushing firms to hire for AI-augmented security functions:

• Phishing detection - 52 % of organizations now use AI models to spot campaigns faster.
• Autonomous triage - 46 % let AI correlate alerts so analysts skip false positives.
• AI-governance leads - a role that barely existed in 2024 but is front-and-center in 2026 as assessment of AI-tool security jumped from 37 % to 64 % year-over-year.

Rather than replace staff, AI acts as a "skills multiplier," freeing humans for threat-hunting, policy design and agent oversight.