This Current Status of AI Adoption article was written by He Xu – Financial Analyst at I Know First

Summary

• AI adoption is increasing and the benefits are substantial with its widespread application in business.
• In addition to adopting more basic and advanced practices, businesses are also using cloud computing more effectively and allocating their AI budgets more wisely.
• Companies take part in a variety of initiatives to mitigate their AI-related risks.

The state of AI in 2021 by Mckinsey Global Servey has been released, showcasing an analysis of AI status for 2021. This survey showcases AI adoption, differentiators of AI, and AI risks.

The results show that the use of AI is still increasing steadily: 56 percent of all respondents, up from 50 percent in 2020, report AI usage in at least one function, especially those in emerging economies, like China, the Middle East and North Africa, increased to 57% from 45% in 2020.

Business Functions of AI: AI is frequently used in service operations, product and service development, marketing and sales, and risk business, which improves marketing budget allocation and spending efficiency for businesses. The top three use cases are service-operations optimization, AI-based enhancement of products, and contact-center automation.

There are two main impacts of AI adoption, increasing the bottom line and saving costs. 27% of respondents in 2021 report at least 5% of EBIT attributable to AI, compared to 22% in 2020. Second, respondents report significantly more cost savings from AI than they did previously in every function, with the most significant changes in product and service development, marketing and sales, and strategy and corporate finance businesses.

What are the Best AI Adoption Programs?

Different companies have different AI programs, which could be differentiated based on practices, AI spending, and cloud use. We assume the respondents attribute at least 20 percent of EBIT to their use of AI as “AI high performers.” Shown as in the following chart, the survey finds that AI high performers are still more likely to engage in most of the core practices and the advanced AI practices more often and use cloud infrastructure much more than organizations seeing lower returns do, which leads to better results and greater efficiency and predictability in their AI spending.

Related Risk Analysis of AI Adoption

Regardless of a company’s AI performance, risk management remains an area where many have room to improve, a shortcoming for the majority of businesses. There are many AI risks, including Cybersecurity, Regulatory compliance, Explainability, Personal/individual privacy, Organizational reputation, Equity and fairness, Workforce/labor displacement, Physical safety, National security, and Political stability.

Survey respondents’ perspectives on risks differ across regions. 57 percent of respondents (versus 63 percent last year) cite cybersecurity as a relevant AI risk in developed economies higher than 47% (versus 59 percent last year)  in emerging economies. In addition, companies in emerging economies focus more on personal/individual privacy, equity and fairness compared with last year.

How to Face the Risks?

Companies are not mitigating all relevant risks because they lack the capacity to address the full range of risks they face and must prioritize. Many companies are struggling with risk management through engaging in risk-mitigation practices, such as model documentation, data validation, and checks on bias. Respondents in emerging economies are more likely than others to wait for clearer regulations to mitigate risk. And they lack the leadership buy-in to devote resources to AI risk mitigation.

I Know First and the Algorithm Trading Market 

I Know First is a Fintech company that provides state-of-the-art AI-based self-learning algorithmic forecasting solutions for the capital markets to uncover the best investment opportunities. I Know First’s service is divided into two levels. Tier I is a daily support forecast based on the client. It shows clients a heatmap of the top bullish and bearish stock picks over various time horizons. Tier II is based on institutions. I Know First’s AI algorithm is used to structure an investment portfolio for Tier II.

The system is a predictive stock forecast algorithm based on Artificial Intelligence and Machine Learning with elements of Artificial Neural Networks and Genetic Algorithms incorporated in it. Based on the relationships and the latest market data, the algorithm calculates its forecasts. Since the algorithm learns from its previous forecasts and is continuously adapting the relationships, it adapts quickly to changing market situations. The algorithms can present patterns based on the data inputs, testing the performance on years of market data, and validating them on the most recent data, which prevents overfitting. If an input does not improve the model, it is “rejected”, and another input can be submitted. I Know First uses algorithmic outputs from the World Indices package to provide an investment strategy for institutional investors.

The investment strategy that was recommended to institutional investors by I Know First accumulated a return of 286.02% which exceeded the S&P 500 return by 278.94%. With this excellent outcome presented, I Know First’s algorithm can be considered as an expert player in finding patterns and trends and making investment decisions more reliable and accurate.

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Conclusion

AI adoption plays an important role in the bottom line and costs savings through the core and advanced practices, as well as leveraging cloud technology. AI is frequently adopted in service operations, product and service development, marketing and sales, and risk business. In addition, many businesses are engaging in a variety of activities to mitigate their AI-related risks, which is a shortcoming of business AI use.