IT's Foretelling: Tech Firms Reveal How AI is Changing Everything You Do
Key Highlights
- The common message from top tech company earnings calls is that AI is simultaneously driving infrastructure growth and creating cybersecurity risks from AI-generated attacks that require even more AI-driven security investment.
- These tech leaders are projecting significant revenue growth based on AI-driven demand.
- The AI boom is forcing enterprises to rethink IT architecture around performance, governance, cost control and operational efficiency.
- Enterprises are moving away from fragmented security environments toward integrated platforms to help reduce vendor sprawl.
AI is simultaneously driving infrastructure growth while also creating cybersecurity risks from AI-generated attacks that require even more AI-driven security investment.
That was the dominant message from recent earnings calls from NVIDIA, Fortinet, CrowdStrike, Qualys, Cloudflare and Check Point Software Technologies. Across networking, cybersecurity and infrastructure markets, executives consistently pointed to AI-driven demand as the primary force fueling growth.
But the message wasn’t simply that AI adoption is accelerating. Executives also described how AI is fundamentally reshaping enterprise infrastructure, increasing operational complexity, expanding attack surfaces and forcing organizations to rethink architecture, governance and security strategies.
The same forces driving rapid growth for these tech vendors are creating new pressures for enterprise IT and security teams, including:
- AI infrastructure expansion.
- Platform consolidation.
- Identity and security modernization.
- Increased demand for automation and operational efficiency.
Executives revealed the key factors creating these pressures:
- More sovereign and regionalized AI architectures. AI infrastructure spending is accelerating at an historic pace, fueled by hyperscalers, increased sovereign AI programs and enterprise deployments.
- Increased AI inference demand. AI inference is the next major growth wave beyond model training, signaling expanding enterprise demand for operational AI infrastructure.
- Increased risks from “AI attack factories.” Cyberattacks are increasingly automated and industrialized through agentic AI systems that can continuously scan infrastructure and generate new attack techniques quickly.
- Shrinking exploit windows. AI is accelerating cyberattack exploitation timelines and increasing pressure on enterprise patching and remediation processes — they must be enacted immediately, not in days or weeks.
Taken together, the earnings calls revealed several major trends IT leaders should prepare for as AI moves from experimentation into large-scale enterprise deployment. Let’s examine them.
AI infrastructure spending continues to grow
AI infrastructure spending continues to expand at an historic pace, fueled by hyperscalers, sovereign AI initiatives and enterprise deployments.
AI and microchip behemoth NVIDIA reported record Q1 FY2027 revenue driven by demand for its Blackwell next-generation data-center platform and GPU architecture powering large-scale AI workloads.
For IT leaders, infrastructure planning is increasingly becoming inseparable from AI strategy.
At the same time, cybersecurity and compliance platform provider Qualys identified AI inference as the next major growth phase beyond model training, signaling broader enterprise demand for operational AI infrastructure rather than purely experimental deployments.
The broader trend suggests that AI spending is no longer concentrated among a small group of cloud providers. IT enterprises are increasingly investing in infrastructure that can support production-scale AI operations.
Enterprises are rethinking IT architecture around AI
The AI boom is also forcing enterprises to reevaluate IT architecture around performance, governance, cost control and operational efficiency. Executives across multiple earnings calls discussed balancing cloud AI deployments with on-premises and hybrid infrastructure to reduce latency, meet governance requirements and better manage costs.
The shift reflects growing demand for integrated AI platforms, optimized networking and more disciplined operational strategies as organizations transition from AI experimentation to operational deployment.
For IT leaders, infrastructure planning is increasingly becoming inseparable from AI strategy.
Cybersecurity vendors are consolidating around AI-native platforms
Cybersecurity vendors are increasingly moving away from standalone security products in favor of integrated, AI-native platforms.
Executives at cybersecurity platform providers CrowdStrike, Fortinet and Check Point Software Technologies all emphasized platform consolidation, automation and AI-assisted operations.
CIOs and CISOs can expect increasing pressure to simplify licensing, consolidate contracts and align cybersecurity spending with subscription-based or flexible usage-based models.
The broader industry shift points toward enterprise demand for platforms that combine endpoint protection, cloud security, identity management, Security Information and Event Management (SIEM), networking and AI-driven analytics into unified environments.
As environments grow more complex, enterprises appear increasingly focused on reducing operational overhead and vendor sprawl.
Consumption-based cybersecurity pricing is gaining traction
Cybersecurity purchasing models are also evolving.
For example, CrowdStrike leaders highlighted growing adoption of flexible licensing and subscription programs, while Fortinet and Check Point Software Technologies also emphasized cross-platform adoption and subscription-based frameworks.
The trend suggests enterprise buyers increasingly prefer flexible, platform-wide spending models over managing numerous standalone contracts and licensing agreements.
Secure networking and SASE remain major priorities
Secure networking and Secure Access Service Edge (SASE) continue to be major IT spending priorities such as hybrid work, distributed infrastructure and AI-driven traffic patterns expand.
Fortinet highlighted strong demand for SASE, sovereign SASE and operational technology (OT) security, alongside continued investment in proprietary ASIC technology and integrated networking-security platforms.
The trend aligns with broader enterprise efforts to modernize branch infrastructure, strengthen hybrid-work security and improve AI-era network segmentation.
The Biggest AI, Networking and Cybersecurity Shifts IT Leaders Need to Prepare For
During their recent earnings calls, executives at NVIDIA, Fortinet, CrowdStrike, Qualys, Cloudflare and Check Point Software Technologies outlined trends that will directly influence enterprise IT priorities. Here’s what they’re signaling:
- AI infrastructure spending is expanding. For example, NVIDIA indicates that enterprises must continue modernizing infrastructure for AI inference workloads, driving ongoing investment in GPU capacity, high-performance networking and AI-ready data center architecture.
- AI is moving into production with AI inference. Qualys and others reveal that AI inference workloads are rapidly becoming operational business workloads rather than isolated experiments. CIOs and CISOs should expect greater focus on AI governance, runtime security, observability and compliance.
- Hybrid AI environments are becoming the norm. Multiple companies are signaling a shift toward balancing public cloud AI services with on-premises infrastructure to control costs, reduce latency and address governance and data sovereignty requirements.
- Cybersecurity consolidation is accelerating. CrowdStrike, Fortinet and Check Point Software are pushing integrated security platforms rather than fragmented point products to reduce vendor sprawl and simplify security management.
- Security procurement models are changing. These same vendors are reinforcing a move toward platform-wide and consumption-based purchasing, creating pressure to simplify licensing, consolidate contracts and use subscription or usage-based models.
OT and critical infrastructure security are becoming more calculated
OT and infrastructure security are also becoming increasingly strategic priorities. For example, Fortinet executives described industrial cybersecurity as both an operational resilience issue and a board-level risk concern for all industrial sectors as systems become more connected to cloud and AI environments.
The shift reflects growing concern that expanding digital connectivity is exposing traditionally isolated operational systems to greater cyber risk.
Vendors warn AI is increasing cyberattack sophistication
Leaders at Cloudflare, Qualys and Check Point Software Technologies also focused heavily on how AI is reshaping the cyberthreat environment.
“The cybersecurity landscape is undergoing a fundamental shift as AI accelerates both the scale and sophistication of threats,” said Cloudflare CEO Nadav Zafrir.
He described two major structural shifts underway.
First, AI is lowering the barrier to sophisticated cyberattacks by democratizing capabilities previously limited to nation-states and highly advanced cybercriminal groups.
Second, cyberattacks are becoming increasingly automated through agentic AI systems capable of continuously scanning infrastructure and generating new attack techniques. Zafrir described these systems as “AI attack factories.”
Qualys executives similarly warned that AI is accelerating exploitation timelines and increasing pressure on enterprise remediation processes.
CEO Sumedh Thakar said attackers using AI can rapidly reverse engineer newly released patches to identify vulnerabilities faster, dramatically shrinking remediation windows.
“The number of detections is going to go up significantly, while the exploit window is going to shrink dramatically,” Thakar said.
The broader implication for enterprise security leaders is clear: Organizations may face larger volumes of faster-moving and increasingly sophisticated attacks, placing greater pressure on automation, detection and response capabilities.
“The number of detections is going to go up significantly, while the exploit window is going to shrink dramatically,” Thakar said.
Why NVIDIA remains central to enterprise AI strategy
NVIDIA continues to sit at the center of enterprise AI infrastructure spending, making its strategy increasingly important for CIOs, CTOs and other IT leaders responsible for long-term infrastructure planning and AI scalability.
Why? Because NVIDIA’s strategy dictates the future of global IT infrastructure.
One of the most significant signals from NVIDIA came from CEO Jensen Huang, who said in a recent commentary that the company “should be growing faster than hyperscale CapEx,” with its AI clouds, industrial and enterprise segment expected to “continue to grow at an incredible pace.”
The statement highlights two major developments in the AI market.
First, NVIDIA’s growth increasingly extends beyond hyperscalers such as AWS, Microsoft, Google and Meta. Demand is now being driven by sovereign AI projects, enterprise data centers, AI-native cloud providers and emerging technology firms.
Second, AI infrastructure spending is broadening across the market rather than remaining concentrated among a handful of major cloud providers.
For enterprise IT leaders, the trend reinforces the growing importance of forecasting AI infrastructure costs, planning data-center capacity and evaluating long-term AI platform dependencies.
Fortinet sees networking and security converging because of AI
Fortinet leaders emphasized growing enterprise demand for integrated networking and cybersecurity platforms as AI expands operational complexity and attack surfaces.
Co-Founder and CEO Ken Xie said convergence of networking and security is accelerating in the AI era.
CFO Christiane Ohlgart added that “as AI rapidly expands the attack surface, customers are prioritizing integrated platforms that share telemetry and reduce operational complexity, accelerating vendor consolidation.”
The commentary reflects broader enterprise demand for consolidated security architectures that improve visibility while reducing operational overhead across networking, cloud and security environments.
The bigger challenge for IT leaders
For CIOs, CTOs, CISOs and other IT leaders, the next phase of digital transformation will not simply be about deploying AI.
As AI is simultaneously driving infrastructure growth while also creating cybersecurity risks from AI-generated attacks, IT will need to manage the infrastructure demands, governance challenges, operational complexity and expanding attack surfaces AI creates.
The technology industry’s largest vendors are making clear that AI is no longer an isolated technology initiative. It’s becoming the foundation reshaping everything IT leaders do.
About the Author
Theresa Houck
Contributor
Theresa Houck is an award-winning B2B journalist with more than 35 years of experience covering industrial markets, strategy, policy, and economic trends. As Senior Editor at EndeavorB2B, she writes about IT, OT, AI, manufacturing, industrial automation, cybersecurity, energy, data centers, healthcare, and more. In her previous role, she served for 20 years as Executive Editor of The Journal From Rockwell Automation magazine, leading editorial strategy, content development, and multimedia production including videos, webinars, eBooks, newsletters, and the award-winning podcast “Automation Chat.” She also collaborated with teams on social media strategy, sales initiatives, and new product development.
Before joining EndeavorB2B, she was an Industry Analyst at Wolters Kluwer in its human resources book publishing operation. Before that, she spent 14 years with the Fabricators & Manufacturers Association, Intl., serving as Executive Editor of four magazines in the sheet metal forming and fabricating sector, where she managed and executed editorial strategy, budgets, marketing, book publishing, and circulation operations, and negotiated vendor contracts.
Houck holds a Master of Arts in Communications from the University of Illinois Springfield and a Bachelor of Arts in English from Western Illinois University.
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