The future in fighting inflation with AI.
In November 2022 in the USA, core CPI inflation, which excludes volatile food and energy prices, was up 0.2% monthly and 6% from a year ago, with economists predicting a 6.1% annual gain. Food prices were up 0.5% month over month and 10.6% year over year. Energy prices fell 1.6% on a monthly basis but are still up 13.1% over the past 12 months. Shelter costs continue to rise, gaining 0.6% compared to October and 7.1% compared to November 2021.
In Poland, a country with a relatively low and stable inflation rate of 2.6% in January 2021, the current CPI coefficient is 17.5 (as of December 2022). Food and energy prices are rising uncontrollably, in a manner unprecedented in recent years.
In both countries, all these factors bring noticeable adverse effects on people’s daily lives and financial capabilities to maintain a comfortable standard of living.
Among other methods and strategies, artificial intelligence (AI) has the potential to revolutionize the way businesses and governments combat inflation. By leveraging the power of advanced algorithms and machine learning techniques, organizations can gain new insights into economic trends and make more informed decisions about monetary policy. With the ability to process vast amounts of data quickly and accurately, AI can help identify potential inflationary pressures before they become a significant problem and take proactive steps to mitigate them.
Let’s look at the various ways AI is being used to fight inflation, both by private companies and on the governmental level.
Companies first - the retail industry is a great example to explore.
The use of AI and IoT in retail has been rising in popularity, mainly as a means to attract customers and improve the user experience. Both technologies are used to increase the personalization of smartphone apps, improve the effectiveness of marketing campaigns and generally optimize productivity. AI also allows retailers to use predictive analytics to help forecast customer purchasing habits while showing users personalized products and services. A retailer can increase or decrease prices based on customer demand patterns in different products, categories, or locations. This strategy helps businesses adapt to changing consumer spending habits faster and reduce costs when and where necessary. With the demand for certain non-essential goods falling due to inflation-related budgeting, companies can decrease their supply accordingly.
Have you heard about the digital twin? It’s a virtual model designed to reflect a physical object accurately. Retailers use digital twins with AI and machine learning (ML) to create sophisticated, virtual simulations of supply chains. Companies can update models with current and real-world data, which helps analyze supply chain systems and identify potential upcoming issues before they arrive. As the AI and ML systems learn, better simulations help predict consumer behavior, analyze inventory and shipping data, and perform supplier stress tests, thus significantly improving a business’ adaptability to volatile market conditions.
Additionally, technologies such as control towers with an AI/ML backbone to power end-to-end visibility into the supply chain allow businesses to understand, act, and get smarter about real-time information, such as shipping delays, inventory production capacity, and sales. Furthermore, there are proven lighter-weight, micro-service-based capabilities in order orchestration that can drive the most optimal available-to-promise order commits and sourcing processes. Thanks to that, the companies can maximize revenue and profits by applying segmentation into order promising and allocation functions, which helps to ensure they stay afloat.
What can governments do?
Well, here, the matter becomes more theoretical. Firstly, governments can use AI-based predictive modeling to analyze large amounts of economic data and identify potential inflationary pressures as early as possible. Then the officials can undertake proactive measures to mitigate inflation before its effects impact households and companies severely. Additionally, AI-based systems can monitor economic indicators and provide early warning signals in case of potential inflationary trends, creating an early warning system that could respond quickly and effectively to inflationary pressures. However, these strategies are more helpful in preventing inflation that mitigating its repercussions.
When inflation appears, suitable governmental entities can use AI to analyze the effectiveness of monetary policy measures, such as interest rate changes and quantitative easing, and make more informed decisions about influencing inflation and encouraging deflation. Furthermore, governments can use AI to optimize logistics and supply chain management to reduce costs, which can help keep prices low and prevent inflation from rising.
Unfortunately, the described ways of AI employment and strategies are not commonly used. It's worth noting that while AI could be a powerful tool to fight inflation, governments are more inclined to use this technology in conjunction with standard economic policies and interventions or forsake it entirely in favor of more traditional means.
AI has the potential to revolutionize the way we combat inflation by providing new insights into economic trends and enabling more informed decision-making. The retail industry is an illustrative example of how businesses can use AI to adapt to changing consumer spending habits, optimize supply chains and reduce costs. Governments can also use AI to predict inflationary pressures, monitor economic indicators, and optimize logistics. However, despite the potential benefits, the use of AI in fighting inflation is still in its early days, and more research and development are needed to realize its potential fully. Do you think that there’s a future in using AI to combat inflation in the national area?
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