A new report has found that 8% of U.K. and and 7% of U.S. decision-makers plan to spend over $25 million (£19.5 million) on AI initiatives this year. This comes after many investors voiced their concerns about the technology’s capabilities and their potential return on investment.
According to the 2024 State of AI report from technology consultancy Searce, a quarter of decision-makers said their organisations were set to spend between $11 million (£8.5 million) and $25 million (£19.5 million) on AI in 2024.
The top reason for making these investments was to drive new business growth, as cited by 31% of U.K. and 35% of U.S. respondents, and this seems to be coming to fruition from their perspective.
Over 90% of U.K. decision-makers surveyed view their AI initiatives as “successful” and nearly a third plan to boost their AI spending by up to 50%. Another 8% said they would see investments increase by up to 100% or more.
The findings are based on a survey of 300 C-suite and senior technology executives at organisations with at least $500 million (£390 million) in revenue conducted in June and July of this year.
The report states that 70% of business decision-makers already have at least three generative AI use cases up and running as a result of their investments. These include tools for customer service, internal research, content generation, marketing and sales, coding, data analysis, and capture.
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However, while 51% of respondents deem their investments “very successful,” just 42% said they were “somewhat successful.”
“The disparity between highly and somewhat successful initiatives suggests a maturity gap in AI implementation,” the report’s authors wrote.
“This presents an opportunity for organizations to focus on talent development, data quality, and robust evaluation metrics to enhance their AI capabilities and achieve greater returns on investment.
Paul Pallath, VP of applied AI at Searce, said in the report, “With AI, organizations frequently focus on short-term, low-hanging fruit, which results in substantial technology and process debt that becomes costly to manage as the organization grows.”
The authors added, “To truly generate ROI, organizations need to move away from blindly investing in these initiatives and hoping for the best, and instead embrace an outcome-centric approach underpinned by proper governance, measurable frameworks and change management processes.”
Respondents were asked about the challenges to AI adoption that most concern them. For U.K. decision-makers, this was the lack of qualified talent, cited by 19%.
The level of “skills-shortage vacancies,” where a job cannot be filled due to a lack of skills, qualifications, or experience among applicants, is very high in the information and communications sector in the U.K. The figure climbed from an already high 25% in 2017 to 43% in 2022, the last year for which data is available.
A recent report also found that the U.K. is the 25th most technically proficient country in Europe, sitting well behind other digital leaders in the region like Germany, France, and Spain.
SEE: Crucial Skills Gaps in the UK Include AI and Strategic Thinking, According to Red Hat
The U.K. government has noted the country’s digital skills shortage and has made a series of key investments in the past year or so to try and address it. In November 2023, more than £200 million was announced to support colleges and universities to offer more training opportunities in industries, including digital.
This March, Science Secretary Michelle Donelan unveiled another package of more than £1.1 billion to fund 4,000 doctorates in engineering and physical sciences.
Microsoft has also made significant investments in bridging the U.K.’s digital skills gap. In December 2023, the tech giant announced a “multimillion pound investment” to provide AI skills training to more than one million people.
The biggest barrier for AI adoption was different for U.S. decision-makers, according to the Searce study, as 20% of respondents said it was data privacy and security. This is linked to apprehension about safeguarding sensitive information, ever-changing regulations, and maintaining client trust.
“This skepticism may stem from high-profile failures or overhyped expectations not being met, leading to caution in AI investments,” the authors wrote. Such high-profile failures may include DPD’s chatbot swearing at customers, Microsoft’s trolling Twitter bot, and Google’s Bard (now Gemini) model answering a question wrong as it was unveiled, wiping $100 billion off Alphabet’s shares.
There is also tangible evidence that AI capabilities are overhyped. A recent Stanford study found that AI is still not as good as humans at the complex tasks of advanced-level mathematical problem solving, visual commonsense reasoning, and planning.
A 2022 report from Deloitte saw the percentage of organisations in the AI “underachiever” category — high deployment/low outcomes — rise from 17% to 22% in a year, suggesting outcomes are lagging.
SEE: Data Scientist Survey: Do Tech Leaders Believe the AI Hype?
Julian Mulhare, EMEA managing director at Searce, said in the report’s press release, “As global investments in AI continue to rise, as our research has found, it is crucial for businesses to focus not just on spending, but on the tangible returns these investments can deliver.”
This point has been emphasised by investors revealing their concerns about when, or if, the huge cash injections into tech companies developing AI models are going to pay off.
Jim Covello, a Goldman Sachs stock analyst, wrote in a June report, “Despite its expensive price tag, the technology is nowhere near where it needs to be in order to be useful … Over-building things the world doesn’t have use for, or is not ready for, typically ends badly.”
Sequoia Capital partner David Cahn argued in a blog post that the AI industry would have to generate a whopping $600 billion a year to pay for its hardware spend.
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According to S&P Global, combined capital spending for Microsoft, Alphabet, and Meta has increased 60% year-over-year as a result of AI investments. Alphabet alone spent $13 billion in the second quarter, 91% more than Q2 2023, putting pressure on profit margins.
But Meta CEO Mark Zuckerberg remarked during the Second Quarter 2024 Results Conference Call that he expects it will be “years” before the company monetises its AI products. Less-than-reassuring comments like this from Zuckerberg played a part in shares in the “Magnificent Seven” U.S. tech companies — NVIDIA, Meta, Alphabet, Microsoft, Amazon, Tesla, and Apple — losing a combined $1.3 trillion over five days in early August.
Furthermore, while business leaders may be excited about the prospect of boosted internal efficiency thanks to AI, consumers do not necessarily share this optimism. A new study from Washington State University found that the presence of the term “artificial intelligence” in a product description actually “decreases purchase intention.”
This is largely due to a lack of trust in AI’s capabilities and the perceived risk associated with elements like loss of control and privacy. Businesses, therefore, should be aware of the ROI of applying AI to their products as well as internal deployment.
