AI hype hits reality roadblock

While there is no shortage of hype surrounding artificial intelligence (AI), businesses are beginning to realise just how difficult it can be to deliver something useful with the technology.

The headline-grabbing revenue of chipmaker Nvidia is an indicator of how much money is being spent on building infrastructure to support AI inference and machine learning workloads, but in reality, many businesses are struggling with the technology.

Nvidia’s latest financial results show that its datacentre business posted $26.3bn revenue in the last quarter, much of which came from sales of AI acceleration hardware to cloud providers, consumer internet businesses and enterprises riding the AI wave.

However, a survey from Sapio Research for Hewlett Packard Enterprise (HPE) found that only one-third (32%) of IT leaders in the UK and Ireland believe their organisations are fully set up to realise the benefits of AI.

The poll of 400 IT leaders in the UK and Ireland for HPE’s Architect an AI advantage report found that while commitment to artificial intelligence shows growing investments, businesses are overlooking key areas that will have a bearing on their ability to deliver successful AI outcomes. These include low data maturity levels, possible deficiencies in their networking and compute provisioning, and vital ethics and compliance considerations. 

Matt Armstrong-Barnes, chief technologist for AI at Hewlett Packard Enterprise, said: “Businesses are investing in AI without first taking a holistic view of the technology and how to implement it. Diving in before considering whether they are set up to benefit from AI and who needs to be involved in its roll-out will lead to misalignment between departments and fragmentation that limits its potential.”

The survey is among a number of new pieces of research that show the gap between AI hype and reality in terms of business outcomes. A separate KPMG poll of UK business leaders reported that despite the promises of generative AI (GenAI), there are significant concerns about its implications for business performance.
 
The business leaders polled in the KPMG survey cited the inaccuracy of results, including hallucinations, as the biggest concern when adopting GenAI (60%). According to KPMG, boards are also worried about errors in the underlying data and information skewing the model’s outputs (53%), as well as problems related to cyber security (50%).
 
KPMG also reported that only 30% of the directors polled said responsible GenAI usage guidelines have been published and communicated throughout their organisation to mitigate these potential issues.

It’s important that companies thoughtfully define a clear AI strategy rather than merely chase the next technological innovation. This strategy should balance the value, cost and risk associated with AI use cases