IT leaders are increasingly trusting AI with business-critical tasks from traffic management to cost optimisation, according to the industry’s most comprehensive report on application strategy.
The latest report from F5, which surveys global IT decision makers, found that 96% of organisations are now deploying AI models, up from a quarter in 2023.
Respondents include 650 IT decision makers from around the globe.They represent organisations of all sizes, from those generating less than $200 million in annual revenue to a significant number of companies generating more than $1 billion annually.
Results show that there is also a growing willingness to elevate AI to the heart of business operations. Almost three-quarters of respondents (72%) said they want to use AI to optimise app performance, whereas 59% support the use of AI for both cost-optimisation and to inject security rules, automatically mitigating zero-day vulnerabilities.
Today, half of organisations are using AI gateways to connect applications to AI tools, and another 40% expect to be doing so in the next 12 months.
Most are using this technology to protect and manage AI models (62%), provide a central point of control (55%), and to protect their company from sensitive data leaks (55%).
Despite growing AI confidence, the report highlights several enduring challenges. For organisations currently deploying AI models, the Number One concern is AI model security.
And, while AI tools are more autonomous than ever, operational readiness gaps still exist as 60% of organisations feel bogged down by manual workflows, and 54% claim skill shortages are barriers to AI development.
Further, almost half (48%) identified the cost of building and operating AI workloads as a problem, up from 42% last year.
A greater proportion of organisations also said that they have not established a scalable data practice (39% vs. 33% in 2024) and that they do not trust AI outputs due to potential bias or hallucinations (34% vs. 27%). However, fewer complained about the quality of their data (48%, down from 56% last year).
APIs were another concern as 58% reported they have become a pain point. Some organisations spend as much as half of their time managing complex configurations involving numerous APIs and languages.
Working with vendor APIs (31%), custom scripting (29%), and integrating with ticketing and management systems (23%) were flagged as the most time-consuming automation-related tasks.
Allied to soaring AI appetites is a greater reliance on hybrid cloud architectures.
According to the SOAS Report, 94% of organisations are deploying applications across multiple environments—including public clouds, private clouds, on-premises data centers, edge computing, and colocation facilities—to meet varied scalability, cost, and compliance requirements.
Consequently, most decision makers see hybrid environments as critical to their operational flexibility. Among respondents, 91% cited adaptability to fluctuating business needs as the top benefit of adopting multiple clouds, followed by improved app resiliency (68%) and cost efficiencies (59%).
In the Asia-Pacific region including China and Japan, nearly half of organisations (49%) are already using AI gateways to connect applications to AI tools, with another 46% planning to do so in the next 12 months.
Among those leveraging AI gateways, the most common applications include protecting and managing AI models (66%), preventing sensitive data leaks (61%), and observing AI traffic and application demand (61%).
Over half (53%) struggle with immature data quality, and 45% are deterred by the high costs of building and running AI workloads.
The hybrid model of AI deployment introduces hurdles, with 79% citing inconsistent security policies, 59% highlighting delivery inconsistencies, and 16% dealing with operational difficulties.
