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Generative AI & eCommerce Evolution or Revolution

Is Artificial Intelligence changing your business?


The world of eCommerce has been evolving rapidly in recent years, with new technologies, tools and platforms constantly being developed to enhance the consumer experience. One of the most significant developments in this space has been the rise of generative AI, which is changing the way we think about everything from product recommendations to customer service. There will be an impact of generative AI on eCommerce but what does it mean for the future of eCommerce.


What is Generative AI?


Generative AI is a type of artificial intelligence that involves using machine learning algorithms to create new data that is like existing data. The most notable example right now is ChatGPT from Open AI. Generative AI can take many different forms, from generating images and videos to creating text and audio content. The key feature of generative AI is that it is able to learn from patterns in existing data and use that knowledge to create new content that is similar in style and structure.



How is Generative AI Being Used in eCommerce?


Generative AI is already being used in several ways to improve the eCommerce experience for shoppers. One of the most common applications is in product recommendations. By analysing a shopper's browsing and purchase history, generative AI algorithms can generate personalised recommendations that are tailored to their interests and preferences. This not only helps shoppers discover new products that they might be interested in, but also makes the shopping experience more convenient and efficient.


Another use in eCommerce is in product descriptions. By analysing existing product descriptions and using natural language processing algorithms, generative AI can create more detailed and compelling product descriptions that help shoppers better understand the features and benefits of a product. This can lead to more informed buying decisions and a better overall shopping experience.


Generative AI can have a major impact customer service for online shoppers in B2C, B2B and marketplaces. By creating chatbots and other automated systems that can interact with customers, merchants can provide instant support and assistance to consumers. This can help reduce the workload of human customer service representatives and improve customer satisfaction. This is not just limited to eCommerce and there is a concern that workers will be displaced.


In addition to these applications, generative AI is also being used to improve inventory management, streamline logistics, and optimise pricing strategies. By analysing data on customer demand and supply chain operations, generative AI algorithms can help logistics and eCommerce companies make better decisions about how to manage their inventory, ship their products, and price their goods.


Let’s look at all those in more detail.


What Are the Benefits for eCommerce?


There are many benefits to using generative AI not just in eCommerce but in many ways within an organisation or business or everyday life scenarios. A concern is that content generated by AI might breach copyright, intellectual property or plagiarize a previous author.

For eCommerce perhaps the most significant is the ability to personalize the shopping experience for individual shoppers. By generating personalised recommendations and product descriptions, companies using eCommerce can create a more engaging and satisfying shopping experience that is tailored to each shopper's unique interests and preferences.


An anticipated benefit of generative AI is the ability to improve efficiency and reduce costs. By automating certain tasks, such as customer service and inventory management, eCommerce companies can reduce the workload of human employees and streamline their operations. This can help reduce costs and improve profitability over the long term.


Generative AI can also help businesses stay ahead of the competition by providing valuable insights into customer behaviour and market trends. By analysing large amounts of data on customer behaviour and preferences, generative AI algorithms can help eCommerce companies make better decisions about product development, marketing, and pricing.


Fact or Fiction some innovations are already here

Personalised Product Recommendations


One of the most significant applications of generative AI in eCommerce is the ability to provide personalised product recommendations. By analysing customer data such as browsing history, purchase history, and demographics, generative AI algorithms can predict customer preferences and suggest products that cater to individual tastes. This personalised approach improves customer satisfaction and increases the likelihood of conversions, ultimately benefiting both shoppers and businesses alike.


Dynamic Pricing Optimisation


Generative AI can also be applied to optimize pricing strategies in eCommerce. By analysing various factors such as demand, competition, and customer behaviour, AI algorithms can adjust prices in real-time to maximize profits and ensure that customers receive the best possible value. This dynamic approach to pricing allows businesses to remain competitive while simultaneously providing an enhanced shopping experience for consumers.


Enhanced Visual Content Generation


eCommerce relies heavily of image and video to grab consumer attention, generative AI can create realistic and appealing product images that capture potential customers. Using techniques such as Generative Adversarial Networks (GANs), AI models can generate product images based on a combination of existing images and descriptions. This capability not only saves time and resources for businesses but also ensures that the visual content on their websites remains engaging and up-to-date.


Chatbots and Customer Support


Generative AI has significantly improved the capabilities of chatbots in eCommerce. By understanding natural language processing (NLP) and learning from past interactions, AI-powered chatbots can provide quick, accurate, and personalised customer support. This not only reduces the burden on human customer service representatives but also ensures that customers receive the assistance they need, whenever they need it.


Inventory Management and Supply Chain Optimisation


By leveraging generative AI, eCommerce businesses can optimize their inventory management and supply chain processes. AI algorithms can predict demand patterns, identify potential bottlenecks, and suggest adjustments to ensure that products are always available and delivered in a timely manner. This not only improves customer satisfaction but also helps businesses reduce costs and maintain a competitive edge.


What are the downside issues for eCommerce?


While generative AI has the potential to revolutionise many industries including eCommerce in many positive ways, there are also some potential negative effects to consider.


Loss of Privacy


Generative AI relies on vast amounts of user data to provide personalised experiences. This can raise concerns about privacy as users' personal information, browsing history, and purchase habits are collected and analysed. The risk of data breaches and unauthorised access to sensitive information can also be a significant concern.


Job Displacement


With the increasing adoption of AI powered systems, there is a possibility that human jobs may be displaced, particularly in customer support, inventory management, and content creation roles. Workers in these areas may need to adapt to new roles or upskill to remain relevant in the job market.


Bias and Discrimination


AI algorithms are only as good as the data they are trained on. If the training data contains biases, the AI systems can inadvertently propagate those biases, leading to unfair or discriminatory recommendations or decisions. This can result in a negative impact on certain customer segments and potentially harm a company's reputation. A good example with ChatGPT is that the data base underlying the system contains content up to September 2021.



Personalisation Black Hole


While personalised recommendations can enhance the shopping experience, excessive personalisation can create a filter bubble, where users are only exposed to products and content that align with their existing preferences. This can limit customer exposure to new or diverse products and reduce opportunities for discovering new interests.


Dependence


As businesses increasingly rely on AI algorithms for decision making, there is a risk of reduced human oversight and intervention. This over reliance on AI systems may lead to unforeseen consequences, such as an inability to adapt to sudden market changes or react appropriately to unique customer situations. Replacing subject matter experts may result in loss of knowledge.


Ethical Concerns


The use of AI generated content, such as images or text, raises ethical concerns about authenticity and intellectual property. It can be challenging to determine the origin of AI generated content and ensure that it doesn't infringe on copyrights or trademarks. Additionally, AI generated content may sometimes be indistinguishable from human created content, leading to concerns about manipulation and deception.


Environmental Impact


As with cryptocurrency mining technology can consume large amounts of resources. Training and deploying generative AI models require significant computational resources and energy consumption. This can contribute to a larger carbon footprint and have a negative environmental impact, such as global warming and resource depletion.


While generative AI offers us as businesses and consumers alike many benefits, it is important to consider and address the potential downsides to ensure that AI technologies are employed responsibly and ethically. Balancing innovation with user privacy, job security, and ethical considerations will be crucial to harnessing the full potential of generative AI in for any business.


Changes in the Board Room


We have yet to see organisations make changes to policies and procedures because of AI. But it will come quickly. The directors and board members of all businesses have an obligation to control the organisation. This is typically done through the chain of command and aligns with the policies and procedures that have been implemented. Just as we have seen sweeping changes due to cyber security risk in the last few years, we will see changes emerge due to the use of AI.


Employees, contractors, directors, and board members work according to agreed job descriptions and procedures. The risks of failure to perform can be managed. AI presents a different set of risks that as yet have not been clearly identified.


Recently a group of senior executives and technology leaders wrote an open letter asking for a hold on development for six months on systems more powerful than Open AI’s GPT-4. The letter was signed by more than 1,000 people including Musk. Sam Altman, chief executive at OpenAI, was not among those who signed the letter. The need is to have the regulatory framework and policy updated to address Generative AI potential impact.


In summary


Generative AI is transforming the eCommerce landscape by offering tailored shopping experiences, dynamic pricing, enhanced visual content, improved customer support, and optimised inventory management. As AI technology continues to advance, we can expect even more innovative applications to emerge, making online shopping more seamless and efficient for consumers and businesses alike. With generative AI at the forefront of eCommerce, the future of online shopping looks brighter than ever.


But the negative potential impacts need to be addressed effectively. Privacy is key to the success of any online service or system and so the protection of private data must be ensured. This must also be aligned with a rigorous regulatory framework with adequate training for technology professionals, board directors, executives and employees.


Author: John Debrincat

Principal Consultant

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