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Taking advantage of the celebration of AppWorld in Madrid, its annual event for partners and clients, F5 has published the 2024 State of AI Application Strategy Report, which reveals that although 75% of companies are already implementing AI, 72% are facing significant data quality problems and an inability to scale data-related practices, something critical for the successful adoption and optimization of AI.
“AI is a disruptive force that allows organizations to create innovative and unique digital experiences. However, the practical aspects of implementing AI are extremely complex, and the company’s risk posture can increase significantly if an appropriate and safe approach is not adopted, says Aran Erel, general director of F5 in Spain. “This report highlights a worrying trend: many companies, in their quest to leverage AI, are overlooking the need to establish a solid foundation. That not only decreases the effectiveness of your AI solutions, but also exposes them to a multitude of security threats.”
Generative AI and challenges of AI implementation
Organizations are excited about the impact of generative AI on their businesses. However, only 24% of organizations say they have implemented generative AI at scale.
While generative AI use is on the rise, the most common use cases tend to serve non-strategic functions. These include copilots and other employee productivity tools (used by 40% of respondents) and customer service tools such as chatbots (36%). However, respondents believe the highest priority AI use case would be workflow automation tools (36%).
When reviewing the challenges of implementing AI-based applications, managers point to three main concerns at the infrastructure layer: 62% cite the cost of computing as a major concern for scaling AI, 57% cite model as a primary concern, and 55% cite performance across all aspects of the model as a concern.
At the data layer, data maturity is an immediate and important challenge affecting widespread AI deployment. 72% of respondents cite data quality and the inability to scale data practices as the main obstacles to scaling AI, while 53% cite a lack of AI and data skills as a major impediment.
Although 53% of companies say they have a defined data strategy, more than 77% of organizations surveyed say they lack a Single Source of Truth for their data.
Cybersecurity as a key concern
According to F5’s study, cybersecurity is one of the main concerns for those tasked with delivering AI services. Factors such as AI-driven attacks, data privacy or data leakage are among the main AI security concerns.
When asked how they plan to defend against these threats to protect AI deployments (or if they are already doing so), respondents say they are focusing on application services such as API security, monitoring, and DDoS and bot protection. Forty-two percent say they are using or planning to use API security solutions to protect data as it moves through AI training models; 41% use or plan to use monitoring tools to gain visibility into AI application usage; 39% use or plan to use DDoS protection for AI models; and 38% use or plan to use bot protection for AI models.
