A new VentureBeat survey has revealed that 70 per cent of companies are experimenting with generative AI.

Most Experimenting and Some Implementing 

The (ongoing) survey which was started ahead of the tech news and events company’s recently concluded VB Transform 2023 Conference in San Francisco, gathered the opinions of global executives in data, IT, AI, security, and marketing.

The results revealed that more than half (54.6 per cent) of organisations are experimenting with generative AI, with 18.2 per cent already implementing it into their operations. That said, only a relatively small percentage (18.2 per cent) expect to spend more on the technology in the year ahead.

A Third Not Deploying Gen AI 

One perhaps surprising (for those within tech) statistic from the VentureBeat survey is that quite a substantial proportion of respondents (32 per cent) said they weren’t deploying gen AI for other use cases, or not using it at all yet.

More Than A Quarter In The UK Have Used Gen AI 

The general popularity of generative AI is highlighted by a recent Deloitte survey which showed that more than a quarter of UK adults have used gen AI tools like chatbots, while 4 million people have used it for work.

Popular Among Younger People

Deloitte’s figures also show that more than a quarter (26 per cent) of 16-to-75 year-olds have used a generative AI tool (13 million people) with one in 10 of those respondents using it at least once a day.

Adoption Rate of Gen AI Higher Than Smart Speakers 

The Deloitte survey also highlights how the rate of adoption of generative AI exceeds that of voice-assisted speakers like Amazon’s Alexa. For example, it took five years for voice-assisted speakers to achieve the same adoption levels compared to generative AI’s adoption which really began in earnest last November with ChatGPT’s introduction.

How Are Companies Experimenting With AI? 

Returning to the VentureBeat survey, unsurprisingly, it shows that most companies currently use AI for tasks like chat and messaging (46 per cent) as well as content creation (32 per cent), e.g. ChatGPT.

A Spending Mismatch 

However, the fact is that many companies are experimenting, yet few can envisage spending more on AI tools in the year ahead which therefore reveals a mismatch that could challenge implementation of AI. VentureBeat has suggested that possible reasons for this include constrained company budgets and a lack of budget prioritisation for generative AI.

A Cautious Approach 

It is thought that an apparently cautious approach to generative AI adoption by businesses, highlighted by the VentureBeat survey, may be down to reasons like:

– A shortage of talent and/or resources for generative AI (36.4 per cent).

– Insufficient support from leaders or stakeholders (18.2 per cent).

– Being overwhelmed by too many options and possible uses – not sure how best to deploy the new technology.

– The rapid pace of change in the generative AI meaning that some prefer to wait rather than commit now.

What Does This Mean For Your Business? 

Although revolutionary, generative AI is a new technology to businesses and, as the surveys show, while many people have tried it and businesses are using it, there are some challenges to its wider adoption and implementation. For example, the novelty and an uncertainty about how best to use it (with the breadth of possibilities), an AI skills gap / talent shortage in the market, a lack of budget for it, and its stratospheric growth rate (prompting caution or waiting for new and better versions or tools than can be tailored to their needs) are all to be overcome to bring about wider adoption by businesses.

These challenges may also mean that generative AI vendors in the marketplace at the moment need to make very clear, compelling, targeted usage-cases to the sectors and problem areas for prospective clients in order to convince them to take plunge. The rapid growth of generative AI is continuing with a wide variety of text, image, voice tools being released and with the big tech companies all releasing their own versions (e.g. Microsoft’s Copilot and Google’s Bard) so we’re still very much in the early stages of generative AI’s growth with a great deal of rapid change to come.