Expert opinions, TECHNOLOGY

When context matters: AI errors have consequences

When it comes to implementing AI systems, businesses can be tempted to use global solutions that span a wide range of markets and customers. However, the local context is extremely important, and businesses run the risk of underestimating this factor.

Language and cultural differences can affect the perception and interpretation of products and services. Deploying global AI-based services without taking into account cultural and linguistic differences can lead to misunderstandings, discontented customers, and loss of markets. Facebook (owned by Meta, recognized as extremist organization and banned in the Russian Federation) has had problems arising from different information privacy laws in different countries. In some cases, companies failed to adapt their data collection and processing algorithms to local laws, which resulted in serious problems with local authorities. Amazon’s AI recommended items that local customers found undesirable or even offensive.

Preferences and needs can vary dramatically from market to market, and global AI-powered products often overlook customers’ need for personalized solutions. Failure to comply with the law can lead to legal consequences and loss of customer trust.

Therefore, it is important that companies thoroughly explore the local context before deploying AI-enabled solutions. This includes adapting technology to specific market needs, ensuring a high level of personalization that takes into account local laws and regulations, and paying appropriate heed to customer feedback. The application of global AI solutions while disregarding the local context can have disastrous consequences for the company’s business and reputation.

Another serious mistake is implementing AI-based services without considering the results. Simply having an AI service does not guarantee success. It is important to apply solutions that are relevant for your business.

For example, a company may decide to implement an AI-powered data analysis system that automatically processes information about customers’ purchases and recommends improvements to the product range. However, despite having this system, the company may stick to its old marketing strategy with no consideration for AI recommendations. As a result, the data obtained from AI remain underrated and the analysis lacks accuracy. Instead of adapting business to new knowledge, the company may continue to rely on its outdated strategy.

Or, for example, a company decides to implement an AI chat bot to process customer inquiries. But staff lacks proper training when it comes to maintaining and supporting the bot. This will lead to poor customer service and low reputation of the company in general.

Despite having AI, companies often continue to rely on older policies and forgo advice offered by AI. It happens for many reasons, including unwillingness to change established operations, uncertainty about new data and simply inertia in decision-making.

Because AI recommendations remain underrated, the data obtained from the system are left without due attention. Analytical conclusions remain inaccurate and the company keeps making decisions based on outdated data and strategies. This may affect the company’s competitive ability and lead to losing market positions.

Like any innovation, artificial intelligence requires very serious research before one begins working with it. The illusion that, once you’ve pressed the button, your business will start to grow rapidly, may cost you a great deal in every sense. To avoid mistakes, it is important to consciously implement AI, train your staff in working with AI data and be ready to adapt business processes based on recommendations offered by AI. Only then will you be able to maximize the benefits and effectiveness of this technology, which will help remain competitive in the market.

By Anastasia Yegorova, experts in digital service development and implementation, including AI technology for businesses, Director of the GetProgress web studio

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