Industry experts forecast a pivotal transformation in enterprise technology by 2026, as organisations increasingly adopt AI-native models at the edge, redefining software procurement, security, and operational architectures amid soaring AI-centric cloud revenues.
Cloud and security executives predict 2026 will mark a turning point in how enterprises buy, deploy and protect software as artificial intelligence reshapes budgets, architectures and risk models.
According to the original report, Rami Houssaini, Chief Cyber Solutions Officer at Cloudflare, said boards were beginning to see limits in centralised cloud and traditional software-as-a-service (SaaS) models as AI demand grows at the edge. “The traditional SaaS model-defined by static features and centralized data silos-is nearing its end. Enterprises are now demanding AI-native, real-time, context-aware services. 2026 will accelerate the shift from “application consumption” to AI-as-a-Service. Organisations will prioritize deploying domain-tuned models at the edge, keeping sensitive data local, and paying for intelligence over software seats. While SaaS won’t disappear, its dominance ends as AI agents become the primary interface for enterprise workflows,” he said. [1]
That forecast reflects a broader commercial pivot already visible in vendor earnings and market analysis. Salesforce this month raised its fiscal 2026 revenue and profit outlook, attributing the upgrade to rapid adoption of AI offerings , notably its Agentforce platform , with AI products contributing materially to recurring revenue growth. Industry data shows AI-enabled revenue lines are becoming a decisive growth lever for large software vendors as enterprises convert pilots into paid deployments. [2][3]
Financial and market research underscores the scale of the transition. A market intelligence report projects AI-as-a-Service (AIaaS) to expand rapidly through the rest of the decade, while investment banks estimate cloud revenues could approach $2 trillion by 2030 with generative AI accounting for roughly 10–15% of that spend. Gartner and other analysts likewise forecast steep increases in AI-optimised infrastructure spending, with inference workloads driving a growing share of IaaS consumption. Together, these figures indicate organisations will need new procurement and consumption models to manage rising, variable cloud bills. [3][4][5]
That economic shift is central to the executives’ argument: buying “intelligence” rather than seats will force vendors to rethink pricing and metering. Houssaini and Rackspace Technology’s Adhil Badat both argue the industry will move from per-user licences to usage-based models tied to AI outputs, requiring finer-grained metering and transparency around how models consume compute and data. “The old way of buying software (SaaS) meant paying a monthly fee for every employee (“seats”) to use a set of fixed features, with all their data locked in a central silo. That model is breaking. In 2026, the focus will shift to AI-as-a-Service. Companies will demand software that is smart, real-time, and customised. They will pay for the actual intelligence and insights the AI provides, not the right to use the program. This move pushes smart AI assistants to the forefront and requires keeping sensitive data secure and close to home. While SaaS won’t disappear, its dominance will end as AI agents become the primary interface for enterprise workflows,” Houssaini said. The company framing of this change implies significant implications for vendor revenue recognition and corporate budgeting. [1][2]
Operational technology and edge deployments are another locus of change. Cloudflare expects Industrial AI to move from passive monitoring to active control of machines and systems, requiring security models that can handle vast numbers of constrained IoT devices. “Think of old factories and power plants (Operational Technology or OT) like a house alarm-they only react after something breaks. In 2026, Industrial AI changes that. AI models will constantly run the show, tuning machines and optimising systems in real-time, moving from watching to driving operations. This sudden level of automation requires a huge security upgrade. Since you can’t install security software on every single robot or sensor (the IoT devices), security needs to become invisible. We’ll see a massive switch to a new security model called Agentless Zero Trust, which checks the identity of every machine interaction instantly and automatically, making the whole network fabric the trusted security guard for automated equipment,” Houssaini said. That agentless approach emphasises network-level inspection and policy enforcement over endpoint agents. [1]
Technologies emerging from the data-streaming and edge networking worlds reinforce the practical contours of the shift. Vendors are packaging streaming-first “agents” that live in event streams and couple real-time data with AI reasoning, while academic and industry research on AI-native edge networks highlights the need for new architectures to coordinate sensing, communication and compute across distributed nodes. These developments point to architectures that place models and decisioning closer to where data is produced, reducing latency and exposure of sensitive information. [6][7]
The convergence of cost, compliance and capability will also reshape governance. Badat said subscription fatigue, multi‑cloud complexity and third‑party AI risk will drive procurement and compliance teams to demand contractual protections for bias, model drift and data use, and to adopt real‑time dashboards for usage, cost and even emissions tracking. Industry analysis supports that requirement: domain-specific models deliver better accuracy and compliance for regulated sectors but demand stronger data hygiene, fine-tuning and ongoing bias monitoring. Organisations, therefore, will need fresh tooling and governance frameworks as they scale from experiments to production. [1][4][5]
📌 Reference Map:
##Reference Map:
- [1] (IT Brief) – Paragraph 1, Paragraph 2, Paragraph 4, Paragraph 5, Paragraph 7
- [2] (Reuters) – Paragraph 2, Paragraph 4
- [3] (SNS Insider / GlobeNewswire) – Paragraph 3, Paragraph 4
- [4] (Goldman Sachs Research) – Paragraph 3, Paragraph 7
- [5] (CIO Dive / Gartner) – Paragraph 3, Paragraph 7
- [6] (Confluent) – Paragraph 6
- [7] (IEEE Communications / TNSE) – Paragraph 6
Source: Noah Wire Services
Noah Fact Check Pro
The draft above was created using the information available at the time the story first
emerged. We’ve since applied our fact-checking process to the final narrative, based on the criteria listed
below. The results are intended to help you assess the credibility of the piece and highlight any areas that may
warrant further investigation.
Freshness check
Score:
10
Notes:
The narrative was published on 10 December 2025, indicating high freshness. No earlier versions of this content were found, and it does not appear to be recycled from other sources. The report is based on recent statements from industry leaders, suggesting original content. The inclusion of updated data and forecasts for 2026 further supports its timeliness.
Quotes check
Score:
10
Notes:
The direct quotes from Rami Houssaini and Adhil Badat are unique to this report, with no earlier matches found online. This suggests the content is original and not reused from other sources.
Source reliability
Score:
8
Notes:
The narrative originates from IT Brief Australia, a reputable source for technology news. However, it is a single-outlet report, which introduces some uncertainty regarding the information’s verification. The reliance on statements from industry leaders like Rami Houssaini and Adhil Badat adds credibility, but their perspectives are not independently verified within the report.
Plausability check
Score:
9
Notes:
The claims about the shift from SaaS to AI-as-a-Service and the adoption of agentless zero trust security models are plausible and align with current industry trends. Similar discussions are present in other recent reports, such as Gartner’s prediction that by 2030, over 80% of enterprises will deploy industry-specific AI agents. ([gartner.com](https://www.gartner.com/en/newsroom/press-releases/2025-09-24-ai-enabling-cloud-services-are-the-future-of-cloud?utm_source=openai)) The narrative’s focus on 2026 forecasts is consistent with the industry’s forward-looking analyses.
Overall assessment
Verdict (FAIL, OPEN, PASS): PASS
Confidence (LOW, MEDIUM, HIGH): HIGH
Summary:
The narrative is fresh, original, and aligns with current industry trends. While sourced from a single outlet, the information is plausible and supported by similar reports from reputable sources. The direct quotes are unique, and the content does not appear to be recycled from other sources. Therefore, the overall assessment is positive.
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