Industry voices discuss the current state of AI, what challenges it faces and what benefits it will deliver in future.
The various potential benefits of using artificial intelligence (AI) within businesses have been widely discussed, but industries have in large part been waiting for the technology available to catch up with the claims of what it will be able to achieve.
While tools based on OpenAI’s ChatGPT large language model (LLM) have proliferated and businesses in various sectors have begun creating task-specific models trained on their own materials, the technology remains nascent and is yet to become ubiquitous or wholly revolutionary.
It is widely accepted that these things will happen, though. In a survey of 386 people as part of GlobalData’s Tech Sentiment Polls Q4 2023 across its network of B2B websites, 92% responded that AI would either live up to all of its promise or that it was hyped but that they could still see a use for it.
And indeed, Jensen Huang, founder and CEO of US tech firm Nvidia, said with the release of the company’s fourth-quarter financial results last week (21 February): “Accelerated computing and generative AI have hit the tipping point. Demand is surging worldwide across companies, industries and nations.”
Views from within industry on whether Huang’s claim that AI has hit a tipping point vary, but there is widespread optimism about what benefits it may bring, tempered as it is with caution about the potential pitfalls.
AI has reached an inflection point
For Michal Szymczak, head of AI strategy at digital solutions provider and Deloitte Fast 50 company Zartis, the technology remains too embryonic to bear out Huang’s claim just yet.
“It would be premature to claim that AI has reached a tipping point,” he says. “Questioning the future of AI is like asking: ‘how broad is our imagination’? Every month, capabilities are growing exponentially. What’s happening at the moment with voice and image generation, for example, has never been done before. Developments will only continue to grow at the same rate.”
This is view to which Dr. Chris Pedder, chief data scientist at AI-powered digital learning provider Obrizum, also subscribes.
“AI has undoubtedly reached an inflection point, though not quite a tipping point,” argues Pedder. “The public is now highly aware of AI’s capabilities and potential. With GenAI so accessible, expect more models trained on abundant human data. Over 50% of data created in 2023 was video, so audio and video generation likely form the next frontier.
“We’re just seeing the first shoots of AI integration into daily life. The true tipping point will be everyday integration across sectors, which remains distant. Focused use cases offer glimpses, gradually normalising applications of AI – for instance, how it’s being used to reshape the corporate learning environment.”
AI’s true tipping point yet to come
The view that public ubiquity of AI is needed before the technology can be seen to have hit a tipping point is one also taken by the co-founder and CEO of the Plus productivity software provider Daniel Li – although Li does believe a tipping point of sorts has been hit.
He explains: “AI has hit a tipping point from an infrastructure perspective, but we have yet to see AI hit the tipping point from a consumer adoption perspective. While all of the big tech companies have now invested billions of dollars into AI, there is still a relatively limited number of apps like ChatGPT that have reached hundreds of millions of users.
“The big question now is whether the bet that consumers will adopt AI will pay off. Over the next year, it will be important to keep an eye on whether consumers are actually using multiple AI tools on a day to day or if the majority of investment continues to be at the “picks and shovels” layer of infrastructure investments.”
Despite some hesitance around the semantics, however, there is widespread agreement that the AI era is now well underway. For many, the starting pistol was fired with the public launch of ChatGPT in late 2022.
AI tipping point a matter of how, not if
Leon Gauhman, chief strategy officer at digital product consultancy Elsewhen touches on exactly this emergence of LLMs in saying: “We have irreversibly entered the age of AI. There are open-source models that democratise the tech, the valuations of AI companies are exponential and the average person in the street has heard of AI.
“However, AI has yet to experience the sort of tipping point event we’ve seen in previous technological revolutions, such as Netscape Navigator’s IPO, which was the starting gun for the growth of the internet economy, or the launch of the iPhone being the breakthrough moment for the mobile era.”
The general consensus is broadly summed up by Peter Wood, chief technical officer at web3 recruiters Spectrum Search, who says: “Across sectors, the integration of AI is no longer a matter of if but how. This transition is characterised by a profound change in how businesses, healthcare providers, and educational institutions leverage data and AI to drive decision-making, innovation, and service delivery.
“The palpable surge in demand across various industries underscores AI’s transition from a niche specialty to a foundational technology, akin to the internet’s evolution in the late 20th century. This is a moment of convergence where technological capability, economic viability, and societal need align, heralding a new era of digital transformation powered by AI.”
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