Firms overconfident on AI strategy, overlook huge blind spots

Nearly half (44%) of IT leaders believe their organisations are fully set up to realise the benefits of AI, but there are critical gaps in their strategies, such as lack of alignment between processes and metrics, resulting in consequential fragmentation in approach, which will further exacerbate delivery issues. 

This is from a new study commissioned by HPE and conducted in January 2024 by Sapio Research. It covered over 2,400 IT decision makers across 14 markets — Australia/New Zealand, Brazil, France, Germany, India, Italy, Japan, Mexico, Netherlands, Singapore, South Korea, Spain, United Kingdom/Ireland, and the United States. 

Findings show that while global commitment to AI shows growing investments, businesses are overlooking key areas that will have a bearing on their ability to deliver successful AI outcomes – including low data maturity levels, possible deficiencies in their networking and compute provisioning, and vital ethics and compliance considerations. 

The report also uncovered significant disconnects in both strategy and understanding that could adversely affect future return on investment (ROI).

“Enterprises in (the Asia-Pacific region) are understandably eager to embrace AI to reap its many transformative benefits,” said Joseph Yang, general manager in charge of HPC and AI for HPE in APAC and India. 

“Yet, as the findings from our survey clearly indicate, many organisations are not yet ready for effective and safe AI deployments,” said Yang. “We are seeing critical blind spots in their AI strategies, including overlooking ethics and compliance, that could lead to serious consequences on the business. 

He added that as AI investments continue to soar, it’s important that organisations devise a holistic AI roadmap that addresses these blind spots to ensure AI success and optimise their ROI.

Strong AI performance that impacts business outcomes depends on quality data input, but the research shows that while organisations clearly understand this – labelling data management as one of the most critical elements for AI success – their data maturity levels remain low. 

Only a small percentage (7%) of organisations can run real-time data pushes/pulls to enable innovation and external data monetisation, while just 26% have set up data governance models and can run advanced analytics. 

A similar gap appeared when respondents were asked about the compute and networking requirements across the end-to-end AI lifecycle. 

On the surface, confidence levels look high in this regard — 93% of IT leaders believe their network infrastructure is set up to support AI traffic, while 84% agree their systems have enough flexibility in compute capacity to support the unique demands across different stages of the AI lifecycle. 

Organisations are failing to connect the dots between key areas of business, with over a quarter (28%) of IT leaders describing their organisation’s overall AI approach as “fragmented.” 

As evidence of this, over a third (35%) of organisations have chosen to create separate AI strategies for individual functions, while 32% are creating different sets of goals altogether. 

As businesses move quickly to understand the hype around AI, without proper AI ethics and compliance, businesses run the risk of exposing their proprietary data – a cornerstone for retaining their competitive edge and maintaining their brand reputation. 

Among the issues, businesses lacking an AI ethics policy risk developing models that lack proper compliance and diversity standards, resulting in negative impacts to the company’s brand, loss in sales or costly fines and legal battles.