An insight into the AI world: The key stats
While some markets, sectors and individual businesses are more advanced than others, the development of artificial intelligence is still in its infancy. Though adoption has been slow in many quarters, there are clear signs that this is accelerating.
According to data insights from Accenture, the number of businesses employing AI will increase “rapidly and significantly”, more than doubling from 12% to 27% by 2024. It also predicts that AI transformation will take less time than digital transformation, forecasting the former to reach 90% of usage precisely 16 months sooner in 2025.
There is a strong monetary incentive to shift to AI, and to do so quickly. The share of companies’ revenue that is ‘AI-influenced’ more than doubled between 2018 and 2021, and is expected to roughly triple between 2018 and 2024, according to Accenture. And a UK government backed study’s findings is evidence of this: suggesting that within the UK private sector, 90% of large organisations have planned or have already adopted AI.
This interest in adoption AI is a relatively new phenomenon. In 2018 only 14% of companies devoted their total technology budgets to AI, according to Accenture. Yet fast-forward three years, the number has doubled (28%), and with this expected to hit over 34% by 2024.
As AI is rising on the list of business priorities, spending in the market is also expected to surge. According to a new IDC report in 2022, worldwide spending in the AI sector will climb 19.6% year-over-year to $432.8 billion (bn) – on its way to breaching the $500bn mark by 2023. By 2028, the market is gossiped to be worth $641.3bn, according to Fortune Business insights.
The sector is home to a variety of new technologies, but what are the most employed types? Unsurprisingly, that depends on the industry, yet perhaps a more widely recognised subclass is chatbots – one of the fastest growing areas within AI.
In its simplest form, a chatbot is a computer program that allows interaction between humans and technology, with around a 92% increase in the usage of chatbots since 2019, according to Drift.
Boost AI added that chatbots are often used as a primary channel for customer service because they allow consumers 24/7 access to brands in a way that’s instant, familiar and conversational. The Norwegian software company speculates conversational technology to inject $112bn in retail revenue by 2023. It also said by 2022, 70% of white-collar workers will interact with a chatbot daily.
Conversational technology can respond to customers instantly; Increase revenue by guiding consumers to products and services that fit their needs; reduce costs by doing the work of multiple employees; Increase employee efficiency; Open up new channels for sales, and bolster brand loyalty.
Often when we think of AI, it provokes memories of sci-fi movies, where it is deployed in tandem with another growing technology: robotics. BCG explored the robotics world and said the potential for new and old players to grow over the next decade has “significant potential”, but established companies manufacturing, particularly, must be both nimble and aggressive.
At the opposite end of the spectrum, startups will be pushing innovation in areas that have the potential to generate high profits and shift the dimensions of the robotics industry. However BCG added that the speed with which they will be able to transform the trajectory of the field remains a wildcard.
In its entirety, forecasts suggest that the sector could be worth as much as $260 bn by 2030. Much of this growth will come from professional services robots that perform useful tasks for humans, such as cleaning, delivering, and transporting.
The publication stated that changing consumer preferences and social trends will accelerate the need for advanced robotics solutions. For instance, consumers are becoming less patient and the surge in demand for faster deliveries will lead to the expansion of robot capacity in manufacturing individualisation and logistics applications.
It also said that, in time, bots will increasingly take over traditionally lower-paying and less skill-intensive jobs.
To ensure the safety of critical infrastructure and technological innovations, enterprises are increasing their AI cybersecurity budgets “significantly”, according to Markets and Markets (MM).
Firms are also aligning business strategies with cybersecurity plans, and initiating cyber awareness programs for employees and customers.
Most recently, the data company added that various programs, such as Global Information Society Project Program on Telecommunication Policy, and strict telecom and regulatory policies have been introduced to regulate telecom and IT cyber threats.
But what should be prized for escalating the growth in cyber security? According to MM, the growing adoption of IoT and increasing number of connected devices are major drivers. Rising cases of cyber threat, growing concerns of data PR – how public relation professionals utilise data and facts to influence public perception about an individual, company, or brand – and increasing vulnerability of Wi-Fi networks to security threats, also explains the increase in appetite for the market. In fact, AI in the cyber security sector is projected to reach $38.2bn by 2026 from $8.8bn in 2019.
Achievers vs Laggards
When it comes to the sectors which are prolific users of AI, Business Insider points to seven industries where UK companies are using AI technology to create a truly global impact: Automotive; Bioscience; Creative Services; Data; Education; Gaming, and Internet of Things (IoT).
According to Next Move Strategy Consulting, the global automotive intelligence market is already well-versed in AI, as it is projected to grow sharply between 2019 and 2030 – from $2.5bn in 2019 to $74.5bn in 2030.
Estimated to generate roughly 1,812 petabytes (PB) of data every year – more than communications, finance, retail and several other industries – manufacturing has become a “blue ocean market” for AI adoption, according to a recent survey by Deloitte. The global AI in manufacturing market size stood at $1.82bn in 2019 and is predicted to reach $9.89bn by 2027.
But where does progression, or lack of, stand with the AI laggards? According to Accenture, financial services and healthcare spring to mind when it thinks of those who are behind-the-times with AI technology.
It alludes to a range of factors that may be contributing to their relatively low AI maturity – including legal and regulatory challenges, inadequate AI infrastructure and a shortage of AI-trained workers, but these are not the only barriers to the adoption of AI.
Data, or better said, an absence of data, is proving a thorn in the side of many industries, according to the BCG. Data is often scarce, as many organisations rely on experienced operators who use intuition to handle changing conditions in a given facility. And the data that does exist, may be of low quality or isolated to individual pieces of equipment, rather than integrated across the entire process.
Data is also often not clean enough and large quantities of data are not necessarily high quality. Quality, in this case, can be used to describe the ease with which a user can obtain useful insights.
Publication Intelligence CIO said it comes down to the oft-repeated truism, ‘Garbage In, Garbage Out’(GIGO) which is as relevant today as it has ever been, and until firms install better software to sort this data they are unlikely begin the AI climb.
Yet there are other significant challenges to companies wishing to adopt smart, cognitive computing processes into their operations. This is born out by the fact that in a McKinsey survey, just 21% of respondents claimed they had rolled out AI in more than one process.
To put simply, some are just resistant to change. Human beings tend to be creatures of habit and, according to think tank Bernard Marr and Co, many do not see the need for AI, or in fact understand what it actually brings to the table.
Perhaps more contentious is the shortage of expert skills in the world of AI. “Talent can be found everywhere, but training opportunities unfortunately cannot,” Ebru Binboga, director of data, AI and automation, IBM UK and Ireland, told ZDNet.
In a recent AI labour market report, technical skills gaps were a concern for many firms. A third (35%) said that existing employees lacking technical skills had prevented them from meeting their business goals, and 49% said that job applicants lacking technical skills had done the same.
Some employers even said that it had restricted or slowed their growth, or prevented them from moving forward with projects.
However, the findings suggested many employers also faced issues with non-technical skills, including in communication, awareness of potential bias around the organisation’s use of AI, and awareness of privacy or ethical issues.
According to Frontiers in Surgery, there is a continuous debate regarding whether AI “fits within existing legal categories or whether a new category with its special features and implications should be developed”.
It stated that to fully achieve the potential of AI, four major ethical issues must be addressed: informed consent to use data, safety and transparency, algorithmic fairness and biases, and data privacy.
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