Firms Not Prepared to Deploy AI Models, Report

Businesses are struggling with the fundamentals of deploying AI models effectively, according to a new Hewlett Packard Enterprise report

Ben Wodecki, Jr. Editor

May 6, 2024

2 Min Read
Data scientists analyze and visualize massive data on virtual screens, using AI to process complex data.
Getty Images

A new Hewlett Packard Enterprise (HPE) report reveals that businesses eager to implement AI are struggling with the necessary processes required to deploy models effectively.

The report, titled Architect an AI Advantage surveyed more than 2,400 IT leaders from 14 countries. Respondents worked at organizations with more than 500 staff and spanned industries including health care, manufacturing and financial services.

HPE found that businesses looking to implement AI are struggling to perform basic processes vital for preparing data for use in AI models.

Findings showed that just 7% of the 2,400 IT professionals surveyed can currently run real-time data synchronization, while only 26% can run advanced analytics applications.

Less than 60% of respondents reported that their business is currently capable of handling functions like accessing, storing and recovering data, which could slow down a model’s development process.

“There’s no doubt AI adoption is picking up pace, with nearly all IT leaders planning to increase their AI spend over the next 12 months,” said Sylvia Hooks, vice president of HPE Aruba Networking. “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.”

Related:HPE, Juniper to Deliver Modern AI Architecture – MWC 2024

HPE warns that businesses failing to address these implementation issues face an increased likelihood of models producing inaccurate outputs.

The report found other gaps, including a failure to understand the levels of compute and networking for running their applications.

Surveyed IT leaders expressed confidence in their outlook, with 93% saying their network infrastructure is suitable and 84% saying their compute storage can meet required demands.

However, HPE’s report saw less than half of respondents admitted to fully understanding the level of demands AI workloads would entail for training and running inference.

Compounding concerns are strategy issues, with over a quarter (28%) of respondents describing their business’ AI approach as “fragmented.”

The report found around 35% of IT leaders said their business has created separate AI strategies for individual functions and 32% said their employer has created different plans altogether.

HPE also found a lack of consideration for ethics in deployments. Around one in four (22%) respondents admitted to not involving their company’s legal teams when building their AI strategies. 

“Misalignment on strategy and department involvement, for example, can impede organizations from leveraging critical areas of expertise, making effective and efficient decisions, and ensuring a holistic AI roadmap benefits all areas of the business congruently,” Hooks said.

Related:HPE Enters AI Cloud Market with Language Model Training Solution

Eng Lim Goh, HPE’s senior vice president for data and AI, said: “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.”

About the Author(s)

Ben Wodecki

Jr. Editor

Ben Wodecki is the Jr. Editor of AI Business, covering a wide range of AI content. Ben joined the team in March 2021 as assistant editor and was promoted to Jr. Editor. He has written for The New Statesman, Intellectual Property Magazine, and The Telegraph India, among others. He holds an MSc in Digital Journalism from Middlesex University.

Keep up with the ever-evolving AI landscape
Unlock exclusive AI content by subscribing to our newsletter!!

You May Also Like