The year 2020 will be remembered for a variety of reasons. It was the COVID year, a year of social transformation and major political transition in the United States. In the tech industry, 2020 will be remembered as the year AI transitioned from scientific fiction to commercial reality.
When COVID-19 arrived in 2020, organisations of all sizes advanced their artificial intelligence (AI) projects. Organizations are focusing on understanding their data and utilising AI to help internal operations now that the epidemic has been in place for more than a year. Years ago, there was an adage that said, “all companies are technology companies,” but that myth has since been debunked. Today, every company is a data company, yet the vast amounts of data necessitate increased automation to uncover critical insights. Enter artificial intelligence (AI) as a potential answer to this expanding issue. AI is attaining a higher level of market maturity, with expenditures increasing by more than 50% year over year, ranging from $500,000 to $5 million each year.
These findings come from the 2021 State of AI and Machine Learning Report released by Appen Limited, a provider of training data used to build AI systems. Appen, in partnership with Harris Poll, surveyed 501 professionals online in March 2021. The respondents consisted of 251 business leaders and 250 data scientists, data engineers, and developers at US-based companies with more than 100 employees.
AI success requires a significant budget commitment
According to the statistics, AI budgets of $1 million or more had a greater chance of AI project deployment than budgets of less than $1 million. Furthermore, budget allocation was linked to obtaining a return on investment (ROI) from AI installations. Forty-eight percent of businesses with budgets ranging from $1 million to $3 million, and 49 percent of organisations with budgets greater than $3 million, reported a deployment rate ranging from 61% to 90%. The figures were substantially lower for companies with less than a million dollars in their budgets.
Budgets also have a significant impact on market leadership perception. Appen broke down organizations into several categories: those spending less than $500,000, those spending $500,000 to $1 million, those spending $1 million to $3 million, and those spending over $3 million. Organizations spending less than $500,000 on AI projects were less likely to consider themselves market leaders compared to the high spenders.
AI is now being deployed as an IT tool
Another significant finding uncovered in the report shows responsibility for AI projects is shifting from business decision makers to technologists. For 39% of organizations, C-level executives were responsible for AI initiatives in 2021, a sharp decrease from 71% in 2020. A rising number of technologists implementing and maintaining projects is an indication that AI is progressing within organizations.
Many businesses are abandoning the notion that AI is a “silver bullet,” instead embedding AI into IT operations. When asked how AI is being used in organisations, 62 percent said it is being used to support internal IT operations, 55 percent said it is being used to better understand corporate data, 54 percent said it is being used to improve productivity and efficiency, and 49 percent said it is being used to aid in the research and development of new products. Reducing business expenses was also at the top of 45 percent of respondents’ lists.
AI success comes from high-quality data
A successful AI deployment always depends on obtaining high-quality data, which is a struggle for organizations both large and small. For this reason, many are turning to external data providers to help with data acquisition, preparation, and management. Organizations with an external data provider were twice as likely to fast-track their AI initiatives compared to those that didn’t have one. In fact, the majority of organizations surveyed have partnered with external training data providers to deploy AI projects at scale.
Working with a data supplier not only allows businesses to deploy more AI initiatives, but it also yields significant ROI. Respondents that utilise an external data source reported a good ROI for 61 percent to 90 percent of their AI initiatives, compared to only 32 percent of those who did not use a provider. Companies that utilise external data sources were also 1.8 times more likely to claim they could solve AI-related privacy and security concerns.
Ethics and interpretability top AI concerns
Despite the fact that companies have embraced AI in the aftermath of the epidemic, the research discovered conflicts between business executives and engineers, mostly around ethics and interpretability. Technologists are more concerned with ethics (41% ) than business executives (33% ), while business leaders are more concerned with interpretability (47% ) than technologists (38 percent ). Nonetheless, business executives and engineers believe that responsible AI initiatives may be implemented using a risk-management strategy.
All the respondents confirmed that their organizations (regardless of size) will continue to accelerate the development of AI post-COVID-19. That’s why organizations are increasingly leveraging training data providers and updating models on an ongoing basis. More specifically, 87% of organizations are updating their models regularly and 91% of large organizations are updating at least once per quarter. Organizations that do this are able to maintain data accuracy and feel they are ahead of the AI game.
AI, in my opinion, has the potential to be the most transformational technology since the Internet. Companies must proceed with caution, allowing AI to address some major problems first, such as enhancing IT operations, R&D, and even some parts of customer service. Once an organisation has acquired experience with AI, understands the risks, and has learned some best practises, it should be aggressive in implementing AI more extensively.
Zeus Kerravala is the founder and principal analyst with ZK Research.