Global market players vying for a larger share of the artificial intelligence (AI) space will have to offer customers differentiated business values in key areas such as trustworthiness.
Companies will want to stand out as organizations are projected to increase their spending on AI, specifically as interest in generative AI (Gen AI) grows.
Also: Generative AI advancements will force companies to think big and move fast
Research firm IDC’s forecast puts enterprise spending on Gen AI solutions at more than $19.4 billion worldwide, including Gen AI software, related hardware infrastructure, and services. This figure is expected to more than double this year before climbing to $151.1 billion in 2027, at a compound annual growth rate (CAGR) of 86.1% from 2023 to 2027.
Asia-Pacific, in particular, will see an “unprecedented surge” in Gen AI adoption, according to IDC, with spending in the region to hit $26 billion by 2027. The researcher suggests Gen AI expenditure for Asia-Pacific is projected to expand at a CAGR of 95.4% between 2022 and 2027.
Also: Enterprises will need AI governance as large language models grow in number
Worldwide, organizations in China are leading in Gen AI adoption, with 83% of businesses in the country currently using the technology, according to a study commissioned by SAS, released last week. In comparison, 65% of businesses in the US have deployed Gen AI, along with 70% in the UK, and 63% in Australia, revealed the survey, which polled 1,600 decision-makers for Gen AI or data analytics implementations in their organizations. The study was conducted by Coleman Parkes Research between February and April this year.
But while China leads in GenAI adoption, this approach does not necessarily equate to effective implementation or better returns, noted Stephen Saw, managing director at Coleman Parkes. “In fact, the US nudges ahead in the race with 24% of organizations having fully implemented Gen AI [tools], compared to 19% in China,” he said.
For now, at least, the US still leads the global marketplace for AI infrastructure, foundation research and development (R&D), startup ecosystem, and VC funding, according to Charlie Dai, Forrester’s vice president and principal analyst for technology architecture and delivery.
In infrastructure, specifically, he pointed to the US’ stronghold in hardware chip design, fabrication integrated systems design, and global cloud infrastructure footprint.
Also: Transparency is sorely lacking amid growing AI interest
The US’ strength in foundation models also spans large language models (LLMs), large vision models (LVMs), and multimodal models, Dai told ZDNET in response to a question on whether China or the US leads the AI market.
However, he said China is rapidly catching up in the development of foundation models, taking the lead in performance for Chinese languages, industry-specific foundation models, and applications in key verticals.
Dai noted that Europe also leads in AI regulations, having passed its AI Act into law in March. He said this is the first comprehensive law on AI, encompassing an ethical framework for AI governance, to be established by a major regulator.
Dai believes the global market is large enough to accommodate leading AI players from both China and the US. He said the technology is evolving rapidly, with many companies in the early adoption stages.
The analyst also pointed to growing tech protectionism that will result in increasingly segregated global tech markets looking for digital sovereignty.
Also: How your business can best exploit AI: Tell your board these 4 things
To gain a competitive edge, he said market players will want to focus on offering differentiated business value to customers, prioritizing AI applications for each industry while reducing complexity for clients at minimum cost.
In particular, he said AI players can gain strategic market share with a stronger play on AI governance.
“By addressing privacy concerns, ethical issues, and ensuring responsible AI use, companies can differentiate themselves in the market and build a strong reputation for trustworthiness,” Dai said.
“This can lead to increased customer loyalty and attract new customers who prioritize these factors when choosing AI solutions.”
He said AI vendors can further facilitate automation in AI governance processes, helping companies streamline their operations and drive revenue growth.
“AI governance can help global AI players gain market share by improving customer trust, preserving corporate values, and driving revenue growth.”
Also: Time for businesses to move past generative AI hype and find real value
The SAS study revealed that just 10% of organizations believe they are fully prepared to comply with impending AI regulations. Only 5% have implemented a reliable system to measure bias and data privacy risks in LLMs.
“With any new technology, organizations must navigate a discovery phase, separating hype from reality, to understand the complexity of real-world implementations in the enterprise. We have reached this moment with Gen AI,” said Bryan Harris, SAS executive vice president and CTO.
“As we exit the hype cycle, it is now about purposefully implementing and delivering repeatable and trusted business results from Gen AI.”
Should adoption take off, research from consultant McKinsey estimates that Gen AI can add between $2.6 trillion and $4.4 trillion to the global economy annually and boost the overall impact of AI by 15% to 40%.
It remains to be seen which global markets will lead the charge in AI but some may face barriers along the way.
Also: Can governments turn AI safety talk into action?
The US Department of the Treasury announced draft rules last month outlawing or requiring notification of some investments in AI and other technology sectors in China. The US government agency said the move was necessary to safeguard national security.
Such restrictions have prompted chipmakers Intel and Nvidia to introduce China-specific AI chipsets with lower specs to remain in compliance with US export sanctions.
OpenAI earlier this month also cut access to its API from China. ChatGPT is not available in the country but its API had remained open to Chinese developers and startups looking to build applications. The move, according to OpenAI, was part of the company’s efforts to block API traffic from regions in which its services were not supported, Reuters reported.
Asked about the impact of limitations placed on China’s access to AI chips and technology, Dai said restrictions by the US government and companies, such as OpenAI, will slow the pace of AI innovation in China and widen the gap between China and US in several areas.
He said these areas include R&D efforts in foundation models by Chinese tech vendors, the AI application startup ecosystem, and AI adoption by industry pioneers in China.
Also: Safety guidelines provide necessary first layer of data protection in AI gold rush
“On the other hand, it will further strengthen China’s resolution to accelerate local R&D for technology self-reliance,” he said. “Tech leaders such as Alibaba Cloud, Baidu AI Cloud, Tencent Cloud, and Huawei Technologies will play a key role in the software and hardware R&D.”
An article from China’s state-owned media, Global Times, also noted that OpenAI’s exit could spur tech players in China to develop local LLMs. The report added the exit will likely drive businesses in the country to move to local models.
As it is, Chinese tech giant Baidu had said it would offer a program to help users migrate to its own GenAI platform, Ernie. Alibaba Cloud also peddled free tokens and migration services to entice OpenAI API developers to move to its LLM platform Tongyi Qianwen, the Reuters report said.
Artificial Intelligence
