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The coronavirus pandemic forced a reduction in information technology costs and the cancellation of many projects. AI projects have weathered the budget cuts better than most, with only a third of those surveyed by Gartner reporting cuts in AI funding. The reason is the transition of AI projects from the stage of piloting to the stage of operational operation. This is facilitated by two main trends in the development of AI solutions – the “democratization” and “industrialization” of artificial intelligence.
They do not spare money on AI
According to a Gartner survey conducted at the end of 2020 among 200 business leaders and IT professionals, during the COVID-19 pandemic, 24% of organizations increased their investments in artificial intelligence, and 42% remained at the same level. Improved customer service and customer retention rates, as well as increasing revenue and optimizing costs, were cited as top priorities for current AI-related initiatives at companies.
Over the next six months, 75% of organizations surveyed intend to develop existing or launch new AI initiatives as they enter the refresh phase (Gartner divides the post-pandemic “restart” process into response, recovery, and refresh; the latter is described as adaptation allowing you to work and develop in new conditions).
Thus, enterprises’ investments in AI have survived despite the crisis. However, according to the survey, the greatest difficulty that prevents the results of such projects from being implemented in production is the inability to assess in advance the real value of AI initiatives for business. Among the respondents, 79% reported that AI projects are in the research or pilot stage in their organizations, and only 21% use AI in “operational mode”.
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Forward down the curve
As noted in Gartner, if artificial intelligence, as a general concept, was placed on the hype cycle chart, it would now slide off the “peak of excessive expectations.” In other words, artificial intelligence tools are starting to meet expectations and bring real benefits to the business. In particular, AI systems come to the rescue during a pandemic: chatbots answer an avalanche of questions related to the disease; computer vision systems help in maintaining social distance, machine learning models are actively used to predict the consequences of various options for restarting the economy in a number of countries.
There are five new positions on Gartner’s new AI hype curve. This is “small data”—data that is small enough to be digested by humans; “generative AI” – software systems capable of creating new content based on existing ones; “composite AI”—machine learning systems optimized by applying a combination of best practices; “responsible AI” – methods and means to ensure compliance with ethics and transparency in the operation of AI systems; “things as customers” are software and hardware systems that can independently select goods and make purchases.
However, like a year ago, tendencies related to the democratization and industrialization of artificial intelligence dominate.
Democratization of artificial intelligence
The topic of artificial intelligence has long gone beyond the academic environment. Today, AI is actively used in practice, making new opportunities available to a much wider range of people – in the business world, these are executives, customers, partners, sales professionals, assembly line operators, IT system operators, and software developers. The latter, as analysts emphasize, will become one of the main driving forces for the development of AI.
With the growth in the use of AI, enterprises have to expand the staff of relevant professionals. The teams building AI solutions include data scientists, data engineers, and developers.
Data scientists look for patterns and design models, while engineering disciplines ensure the stability, reliability, and security of first-designed mechanisms, enabling the creation of large-scale AI systems. Tools that simplify and speed up the implementation of such systems for engineers are designated on the hype cycle as “AI developer and teaching kits”.
Industrialization of AI platforms
With industrialization, the range of applications of AI platforms is expanding, their scalability is growing, and security is improving, analysts say. According to a Gartner survey, AI projects in industrial enterprises are often led by top managers: for example, CEOs are at the helm of almost 30% of initiatives. This contributes to the accelerated implementation of systems, including through faster funding. Find more information at https://unicsoft.com/.
