Around 75% of enterprises push through with AI deployment despite 72% reporting significant data quality issues and an inability to scale data practices, according to F5’s 2024 State of AI Application Strategy Report.
“Our report highlights a concerning trend: many enterprises, in their eagerness to harness AI, overlook the need for a solid foundation. This oversight not only diminishes the effectiveness of their AI solutions but also exposes them to a multitude of security threats,” said Kunal Anand, EVP and CTO at F5.
Implementing AI at scale
The study revealed that only 24% of organisations say they have implemented generative AI at scale. The most common use cases include copilots and other employee productivity tools (40%) and customer service tools such as chatbots (36%).
Roadblocks
Enterprises cite the cost of compute (62%), model security (57%), and performance across all aspects of the model (55%) as major concerns to scaling AI in the infrastructure layer.
Moreover, respondents cite data quality and an inability to scale data practices (72%), lack of AI, and data skillsets (53%) as the top hurdles to scaling the technology in the data layer.
The study also revealed that cybersecurity is a principal concern for AI delivery. Enterprises are planning to bolster their defenses through a range of security measures, including API security solutions (42%), monitoring tools for visibility into AI app usage (41%), DDoS protection (39%), and bot protection for AI models (38%).
“AI is a disruptive force, enabling companies to create innovative and unparalleled digital experiences. However, the practicalities of implementing AI are incredibly complex, and without a proper and secure approach, it can significantly heighten an organisation’s risk posture,” Anand said.
