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AI • January 20, 2023

How AI Drives Business During a Recession

The global slowdown leading to rapid deterioration of growth prospects, rising inflation, and tightening financial conditions marks the beginning of a recession. Businesses across industries will need to prepare in advance in order to mitigate the challenges posed by the imminent recession.

While each industry will experience a recession in different ways, the most common challenges faced by companies of all sizes include:

  • Reduction in quality of products and services: As declining sales will no longer be able to pay for the cost of doing business, businesses may look to find wiggle room in the operating budget. This could drive the urge to cut down on product size, quality, and benefits or raise product prices.
  • Dwindling capital to pay employees: During a recession, companies may shelve plans to expand operations, pay bonuses or even keep the workers they have.
  • Lower employee morale and productivity: Frequent layoffs and employees being asked to do more with less can lead to an overall culture of apprehension. Productivity tends to suffer when employees feel uncertain and unmotivated by bad news.

AI helps businesses thrive, not just survive

According to a recent report on corporate technology budgets for 2023 by Forrester Research, global unrest, supply chain instability, soaring inflation, and the long shadow of the pandemic - all point to an economic slowdown. It further cautions that slower overall spending along with turbulent and inconsistent employment trends will make it difficult to navigate planning and budgeting during 2023. The report advises businesses to adopt methods to reduce spending, including doing so by getting rid of outdated technology. However, when it comes to investing in AI, the report firmly suggests that companies should increase their spending.

A key insight for organizations looking to navigate the impending recession is that technology is a business driver, not a cost center. Businesses need to focus on areas like cloud computing, machine learning and artificial intelligence, and automated processes for investments. While investing in such technologies may seem to have high upfront costs, they can maximize profits and reduce risks in the long term. 

How can AI help during a recession?

AI spearheads the technology-driven approach that sets a business apart and consolidates its competitive edge during difficult times due to its considerable impact on reducing costs, optimizing financial functions, and finding new revenue streams.

AI can help organizations drive business growth during a recession by focusing on the following key areas: 

  1. Predictive Analytics and Targeted Marketing:

In a market filled with uncertainty, AI can help businesses collect and connect data to provide clear insights. This is especially helpful to create innovative marketing campaigns tailored to every customer's needs. AI-powered data-driven analytics not only lend deeper insights into purchasing trends and preferences but also enable organizations to build relevant products that address the needs of the market.

Companies can leverage AI to collect a wide range of data including current market trends, business drivers, customer demographics, search history, current events, and even weather conditions. The data collected can be employed to curate personalized and strategic interfaces like the dynamic demand forecasting model and dashboard that help decision-makers with detailed predictions for the future along with recommendations. This data-driven approach helps businesses accelerate traffic while reducing customer churn.

AI-powered hyper-personalization to deliver unique and memorable user experiences is another use case of AI. Personalized recommendation systems provide users with a hyper-personalized experience based on their past purchases, brand interactions, and interest in similar products. This keeps users engaged and serves as an invaluable source of information for companies on current market trends and user behavior. Not surprisingly, 87% of marketers have reported positive results from their personalization efforts.

In the healthcare industry, AI and ML-based solutions like disease recurrence prediction and disease detection using medical imaging are gaining prominence. These solutions help optimize processes for large hospitals and advance clinical outcomes for patients. As a result of continuous technological advancements in the industry, such as Google MDE and Alphafold, it is now possible to build advanced deep-learning models for tumor recognition and brain hemorrhage detection that can identify the type and location of a tumor or hemorrhage from a CT scan.

  1. Intelligent Workflow Automation:

An important strategic aspect of negotiating the recession is to manage resources efficiently and spend prudently. While many companies will be forced to lay off support staff, it is imperative that they instead focus their energies on maximizing their current resources.

For most banking and insurance companies, tasks like reviewing documents, reconciling invoices, and processing payments take notoriously long periods of time and can often hinder the normal flow of business. Automating repetitive and mundane tasks like data entry and document processing has several cost-saving benefits, from reducing overheads to minimizing costly and time-consuming human error. Additionally, with the recession comes a decrease in hiring which can negatively impact the efficiency of existing employees. In such situations, AI can be leveraged in applications like automated invoice and mortgage processing to reduce the workload and ensure seamless handling of customer documents.

Manufacturing and automobile companies generally encounter quality and inspection-related issues during times of recession. It becomes increasingly difficult to allocate resources to handle every minor detail in the manufacturing process. However, it is imperative to ensure that important quality checks are not neglected despite a reduction in available resources. Smart solutions like engine defect detection can help remedy quality issues with maximum accuracy by leveraging visual inspection AI to build defect classification models. Companies can also integrate AI in predictive maintenance for anomaly detection and warehouse inventory count automation to accelerate operations while limiting human error. 

  1. AI-powered Customer Support:

A major challenge for businesses during recessions is the constrained capacity to serve customers better. Expectations are usually sky-high when it comes to customer support and services. It will certainly be a challenge for companies to meet these expectations during a recession. 

AI helps companies deliver personalized contact center services which in turn greatly improve brand reputation and can help the business grow exponentially. According to a recent survey, 41% of consumers prefer chat support as they believe that their issues will get resolved faster. AI-based solutions provide further support by tracking these conversations in real time. The level of insight generated can help determine peak business hours, the optimum number of agents required, and the type of support customers prefer (chat or phone). Businesses can further use it to provide feedback to their customer support agents to optimize their operations.

Navigate the recession with Quantiphi’s expertise in AI

Although the short-term future may seem bleak, the role of AI in helping businesses mitigate the hurdles of an economic recession is evident. Businesses must seek to leverage AI in order to maximize efficiency and ensure continuous growth. As an AI-first digital engineering company, Quantiphi combines unparalleled industry expertise, disciplined cloud and data-engineering practices, and cutting-edge AI and ML capabilities to ensure our customers stay ahead of the curve, no matter how uncertain it may be. 

Get in touch with our experts to learn more about how you can mitigate the challenges posed by the recession with AI. 

Muskan Gupta And Srijamya Ranjan

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Muskan Gupta And Srijamya Ranjan

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