F5 (NASDAQ: FFIV) has released a new report providing unique insight into the current state of AI adoption in the enterprise. According to F5's 2024 AI Application Strategies Report, 75% of enterprises are implementing AI, but 72% are grappling with significant data quality issues and an inability to scale data operations.
Effectively deploying and optimizing AI depends on the quality of data and the robustness of the systems used to capture, store and protect that data.
“AI is a disruptive force, enabling enterprises to create innovative and unparalleled digital experiences. But the reality of implementing AI is incredibly complex and, without the right, secure approach, can significantly increase an organization's risk posture,” said Kunal Anand, EVP and CTO, F5.
“Our report highlights a worrying trend: many companies are so eager to embrace AI that they are overlooking the need for a strong foundation. This oversight not only reduces the effectiveness of their AI solutions, but also exposes them to a variety of security threats.”
As enterprises develop new infrastructure to support the expansion of AI-powered digital services, the study highlights challenges across infrastructure, data, model, application services and application layers that must be addressed for widespread, scalable deployment.
Promise and reality of generative AI
Organizations are enthusiastic about the business impact of generative AI, calling it the most exciting technology trend for 2024. However, only 24% of organizations have implemented generative AI at scale. The most common use cases for generative AI tend to be for less strategic functions, such as copilot and other employee productivity tools (used by 40% of respondents) and customer service tools like chatbots (36%). Workflow automation tools (36%) were identified as the highest priority AI use case.
Enterprise leaders cite three main concerns at the infrastructure layer when scaling AI-based applications:
- 62% cited the cost of computing as a major concern.
- 57% cited model security, with company leaders planning to spend 44% more on security over the next few years.
- 55% are concerned about performance across all aspects of the model.
At the data layer, data maturity becomes a more immediate and significant challenge.
- 72% of respondents cited data quality and lack of scalability of data operations as their biggest obstacles.
- 53% said a lack of AI and data skillsets is a major obstacle.
- While 53% of companies have a defined data strategy, over 77% lack a single source of truth for their data.
Cybersecurity remains a major concern
Cybersecurity is a top concern for those providing AI services, with AI-enabled attacks, data privacy, data leaks, and increased liability cited as the top concerns. To protect against these threats, respondents are focusing on app services such as API security, monitoring, and DDoS and bot protection.
- 42% are using or planning to use an API security solution.
- 41% use or plan to use monitoring tools to gain visibility into AI app usage.
- 39% use or plan to use DDoS protection for their AI models.
- 38% are using or plan to use bot protection for their AI models.
