A recent report by Hewlett Packard Enterprise (HPE) unveils challenges faced by businesses in effectively deploying AI models. Titled "Architect an AI Advantage," the report surveyed over 2,400 IT leaders across 14 countries, representing various industries.
The report highlights that many businesses are encountering difficulties in executing essential processes crucial for AI model deployment. Only a small fraction, 7% of the surveyed IT professionals, can presently conduct real-time data synchronization. Additionally, merely 26% have the capability to run advanced analytics applications.
Sylvia Hooks, Vice President of HPE Aruba Networking, emphasizes the increasing adoption of AI while acknowledging existing challenges. She notes, "These findings clearly demonstrate the appetite for AI, but they also highlight very real blind spots that could see progress stagnate if a more holistic approach is not followed."
HPE warns that businesses neglecting these implementation challenges are at risk of generating inaccurate outputs from their AI models.
The report identifies gaps in understanding the compute and networking needs for running AI applications. Although surveyed IT leaders express confidence in their network infrastructure and compute storage, less than half fully comprehend the demands of AI workloads for both training and inference processes.
Approximately 28% of respondents describe their organization's AI approach as "fragmented." This fragmentation is evident in the creation of separate AI strategies for individual functions by 35% of IT leaders and entirely different plans by 32% of employers.
The report also notes a lack of consideration for ethics in AI deployments, with 22% of respondents admitting to not involving their company's legal teams in building AI strategies.
Eng Lim Goh, HPE's Senior Vice President for Data and AI, underscores the importance of understanding gaps across the AI lifecycle. He states, "Businesses must carefully weigh the balance of being a first mover and the risk of not fully understanding the gaps across the AI lifecycle, otherwise the large capital investments can end up delivering a negative return on investment."
The report concludes by highlighting the necessity for businesses to address these challenges comprehensively to ensure successful AI implementation and maximize the benefits of AI technologies.
