As demand increases for AI solutions, the competition around the huge infrastructure required to run AI models is becoming ever more fierce. This affects the entire AI chain, from computing and storage capacity in data centres, through processing power in chips, to consideration of the energy needed to run and cool equipment.
When implementing an AI strategy, companies have to look at all these aspects to find the best fit for their needs. This is harder than it sounds. A business’s decision on how to deploy AI is very different to choosing a static technology stack to be rolled out across an entire organisation in an identical way.
Businesses have yet to understand that a successful AI strategy is “no longer a tech decision made in a tech department about hardware”, says Mackenzie Howe, co-founder of Atheni, an AI strategy consultant. As a result, she says, nearly three-quarters of AI rollouts do not give any return on investment.