(Yicai Global) Aug. 18 -- Artificial intelligence is undergoing massive adoption globally as the Covid-19 pandemic has triggered its first-time deployment in many businesses, one study has found.

Some 74 percent of companies around the globe are now exploring or deploying AI, but stand at various stages of its implementation, New York Times Business Bestselling author, futurist, and columnist Chuck Martin wrote on July 30 in The Yuan, an AI-centric open community whose avowed mission is to put the ‘All-Inclusive’ into AI for the commonweal.

The Global AI Adoption Index 2021, compiled by US-based market researcher Morning Consult for American tech behemoth IBM, canvassed Information Technology decision makers in 5,500 businesses in the US, China, India, Singapore, UK, Italy, Spain, France, Germany, Brazil, Mexico, Colombia, Argentina, Chile and Peru, per the study The Yuan cited in its report.

Several causes underlie this burgeoning application of AI: shifting general business needs, the ever-greater accessibility of this continuously advancing technology, along with a heightened desire for contactless interaction and other commercial imperatives the coronavirus has wrenched into a new orientation.

One-third of companies are analyzing data to build and scale AI in their business operations, the survey concluded, though they have yet to deploy any AI projects, while another one-third use pre-fab apps like chatbots.

Someone-quarter of firms are developing proofs of concept for their AI-based or -assisted projects, while a further one-fourth are probing AI solutions, but not yet buying any tools or apps. One echelon has progressed beyond the PoC stage, with 21 percent activating the transformative heuristic technology across their entire business spectrum. These are companies with a head start that forged ahead into the teeth of the pandemic. They are in a set range of industries, like H&M in retail and EasyJet in transport, both of which have taken a company-wide approach to AI-ization.

“IT professionals in China and India were more likely to report their company plans to invest in each area of AI, especially in proprietary AI solutions, embedding AI into current applications and processes and off-the-shelf tools to build their own applications and models,” Morning Consult reported.

More than 50 percent of Chinese organizations will add AI capabilities to their incoming call processing systems this year, per a November prediction by US market intelligencer International Data Corporation. Forty-five percent of repetitive tasks will also become automated or augmented by ‘digital workers’ backed by AI, robotics, and robotic process automation in the world’s most populous nation by 2024, IDC also projected.

Aiming High

This style of company-wide approach requires total buy-in from the apex of an organization, as the resources and investments consumed may be considerable. Any business seeking to take this tack should strive for short-term successes to quickly grandstand its edge to top company brass.

Short-term wins are thus the fuel for successful long-term implementation, but the key to these gambits is to stay true to the long-haul strategy lest a company's AI approach should become too heavy on tactics and too light on strategy and thus blight the prospects of greater long-term gains.

AI deployment in business varies widely from country to country. The most activations are in China, followed by India, Singapore, Italy, the US, and Spain, according to the IBM-commissioned study. Every company surveyed was exploring AIbutstood at different levels of deployment. Even more AI inaugurations beyond the PoC stage thus loom on the horizon worldwide.

One of the most intractable barriers to AI adoption, afflicting 39 percent of businesses, per the IBM survey, is a dearth of AI expertise or knowledge in the market, a common gripe among AI sector mavens. AI’s eruption into businesses in every sector has simply drained the pool of talent available for hire.

Other hindrances are increasing data complexity and data silos (32 percent) -- bins of fixed data under the control of one department shut off from the rest of an organization that tends to emerge in big outfits because each unit has varying aims, priorities, and duties, or where departments compete rather than working together to achieve joint business objectives, so organizations are striving to eliminate these data hoards -- and the lack of tools or platforms to develop AI models (28 percent).

These factors also vary by company size, with rising data complexity and numbers of data silos being the most obdurate obstacle for larger firms, 11 percent more so than for their more diminutive counterparts.

Companies going the AI road must anticipate and plan for setbacks along the way. AI activations can be tricky and rife with unintended consequences unless these are foreseen. Testing is thus a critical precursor to a full-scale rollout. Difficulties companies cite include analyzing data to build and scale trusted AI (39 percent), infusing AI throughout the business (37 percent), organizing data to create a business-ready analytics foundation (37 percent), and collecting data to simplify it and render it more accessible (37 percent).

Diffusional Difficulties

Larger companies are more challenged with plugging in data analysis and diffusing it to permeate their entire organizations, while smaller companies find data collection the biggest snag. One key factor is closely watching the data being used and ensuring that humans are integral to the course of AI deployment to check and double-check data, and to monitor for potential biases, above all. Despite pitfalls large and small, firms around the world are plowing ahead pell-mell with AI.

Nearly half (43 percent) of global information technology professionals say Covid-19 has added impetus to their companies’ AI rollouts, with larger firms being 31 percent more likely than smaller ones to so state. Businesses stalled in trialing or embedding AI will lag those already on the path. Pandemic-shifted business needs caused companies that had already started with AI to tend to redouble their efforts, while many less advanced ones inclined to fail to follow through on theirs.

The IBM-led study also found that one-third of global IT professionals plan to invest in the following areas: embedding AI into current AI applications and processes, reskilling and workforce development, off-the-shelf AI apps, proprietary AI solutions, and off-the-shelf tools to build their own apps and models.

Companies are poised to funnel AI investments into data security, followed in descending order by automaton of processes, customer care, virtual assistants and chatbots, business process automation, fraud detection, sensor data analysis, AI monitoring and governance, marketing, supply chain and personal security over the next year, the IBM study also concluded.

One of the most popular tracks savvy companies follow is to start by using AI to automate processes, thus freeing up time for people trapped in repetitive tasks ripe for automation. The most visible market impact will be in automation regardless of the speed of AI adoption and/or the effects of geographic factors. Chatbots, automated billing and payment systems, and automated internal processes are proliferating alongside a mass migration to a self-service customer model across the board.

Savvy businesses should focus their attention and concentrate their energies here to catch the AI wave.

Editor: Tom Litting, Kim Taylor

Yicai Global is pleased to announce its cooperation with The Yuan (https://www.the-yuan.com) and looks forward to future feature articles from it authored by luminaries of the ilk of Hippo. AI founder Bart de Witte and the many other leading lights in the AI sector who are its regular contributors. The Yuan provides an open community with the aim of averting the emergence of bias and social inequities and inequalities arising from uneven access to AI and, as such, its philosophy closely aligns with Yicai Global’s own stance.