Nearly half of IT leaders believe their organisations are fully set up to realise the benefits of Artificial Intelligence (AI); yet, only 57% set one single consolidated strategy, a report commissioned by Hewlett Packard (HP) finds.

The findings reveal that there are “critical gaps” in these organisations’ strategies, such as a lack of alignment between processes and metrics, which then leads to consequential fragmentation in approach, which will further exacerbate delivery issues.

The report, ‘Architect an AI Advantage’, which surveyed more than 2,000 IT leaders from 14 countries, concludes 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. 

These areas include low data maturity levels, possible deficiencies in their networking and compute provisioning, and vital ethics and compliance considerations. Moreover, there seems to be a significant disconnect in both strategy and understanding that could adversely affect future return on investment (ROI).

“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, VP, 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,” explains Hooks. 

Misalignment in strategy and department involvement can impede organisations from leveraging critical areas of expertise, making effective and efficient decisions, and ensuring a holistic AI roadmap benefits all areas of the business congruently.

That said, fewer than 6 in 10 respondents said their organisation is completely capable of handling any of the key stages of data preparation for use in AI models – from accessing and storing, to processing and recovering. 

This kind of discrepancy increases the probability that the model will deliver inaccurate insights and a negative ROI.

Gartner expects “GenAI will play a role in 70% of text- and data-heavy tasks by 2025, up from less than 10% in 2023.” 

Less than half of IT leaders admitted to having a full understanding of what the demands of the various AI workloads across training, tuning, and inferencing might be.

“AI is the most data and power-intensive workload of our time, and to effectively deliver on the promise of GenAI, solutions must be hybrid by design and built with a modern AI architecture,” said Dr. Eng Lim Goh, SVP for Data & AI, HPE.

However, as businesses attempt to understand the hype around AI, without proper AI ethics and compliance, businesses run the risk of exposing their proprietary data.

There are also other risks, as the quality of the outcomes from AI models is limited to the quality of the data they ingest.