The evolution of the internet and digital technology has sparked new opportunities for trade, expanded product lines, and improved customer experiences. As #artificialintelligence becomes a practical technology in industries, it is worthy to note that many businesses are still playing catch-up, while figuring out how it can transform their operations.

Consequently, there is a slow transition from traditional business models to technology-enabled enterprises. I believe that AI has come of age, and today all industries can start to adopt machine learning into their product lines. The National Security Commission on Artificial Intelligence (NSCAI) shared similar sentiments about AI investments, during their recent conference.

Standing out among all industries, e-commerce has led the way for AI adoption. From Amazon and eBay to Alibaba’s payment integrations, AI technology is optimizing operations and increasing organizational competition.

Like most industries, the retail sector depends on a host of factors such as technology, customer satisfaction, and sales rates among others as businesses race towards capitalizing on market demand.

2019 saw more AI investments in e-commerce; from #chatbots, to market prediction tools and information systems upgrades, to keep businesses ahead of the curve.

Estimates show that AI investments in e-commerce will continue on an upward trajectory in the coming years totaling to a Compound Annual Growth Rate of 42.8% from 2019–2025. Such a high CAGR in the e-commerce sector speaks volumes about the exciting days ahead of this industry.

From a growth perspective, we should expect #ecommerce companies to continue developing more AI-related applications to boost their operations and raise market performance in areas including promotion of products, customer management, and advertisements.

Before we proceed, let’s ponder on this question: How can e-commerce businesses take advantage of the expanding technological ecosystem such as AI to boost their performance and drive growth? By considering this question, we shall have a clear idea of the current AI space in the e-commerce sector and better forecast conclusions about what the future holds.

AI Technology Applications in E-commerce

Natural language processing technology is an AI application used in e-commerce where retail companies provide customers with information about products and services. Whether you are looking for a product on an Etsy website or Shopify, you need real-time results that give you options about the purchase you want to make. NLP makes this possible as customers can navigate easily within the online shop and successfully add items to their cart. Every customer wants a smooth shopping experience and NLP makes everything fall into place.

Natural Language Processing works in e-commerce by evaluating customer data and boosting their shopping experiences.

These insights are best captured in the research paper by Ehsan Toreini about trusting AI applications in business alongside #ML technologies that harness these technologies in industries. Accordingly, complaints from customers on products is another area served by NLP where the technology assists buyers to communicate with the support team. Responses take less time as customers wait for directions on issues facing them and this determines the success of a retail operation.

Chatbots have become commonplace as we use them on a daily basis for asking questions and support. A recent Gartner Research estimates that chatbots will increase in 2020 as online shoppers find the convenience of buying products or services.

Unlike human agents, chatbots enable customers to find products easily and make the right decisions.

E-commerce companies have taken advantage of machine learning algorithms to train these bots on all customer queries. As such, bots provide answers on the spot and have been trained to engage with customers online. We can, therefore, see that AI applications have become commonplace in the e-commerce sector as companies focus on customer satisfaction, sales management, and leads. It is no coincidence that an estimated 70% of customers will engage directly with bots according to findings by Mashable in the year 2022.

We cannot mention the practicability of AI in e-commerce without considering relationship building with customers. As customers shop online, they input personal information and interests, which in turn is generated by AI for the support team to analyze. For example, a customer who likes shopping for electronics above $300 and prefers specific attributes in the product is well understood by the #AI technology, which then transmits the right data leading to better decision-making.

Retail companies benefit from data as they use trained systems to interpret the information by showing trends and even projecting future prospects. With large data sets growing daily, online retailers must figure out the best technology to use for making sense of the numbers and this is where AI comes in. AI not only offers insights about the current trends but also, creates an avenue for trend mapping which is critical to the success of e-commerce companies.

Foundational Frameworks of AI in E-commerce

Let’s face it: Every organization needs a strategic data plan on AI as market competition heats up. Without a clear analytics roadmap, e-commerce companies cannot derive value from customer data and calls for re-organization of priorities such as new engineering skills alongside data science.

A recent poll from CB Insights shows that e-commerce companies are increasing their investments in AI. For example, the demand for data scientists in corporate organizations has increased with a view of building a strong market presence. Ideally, focusing on the analytics area ensures that e-commerce companies can implement their AI strategy because of using the right data. Al investments in e-commerce platforms come down to a good analytics plan and data management as this sets them apart from competitors.

Relying on data from fragmented points is a problem for most enterprises as they implement AI investments. By extension, companies fail to understand their data plan hence missing the benefits of AI.

AI does not make sense without data and organizations should be cautious about their data plans such as accessibility.

Sometimes, the resource constraint holds back enterprises from developing an integrated data plan leading to failed results. The idea of perishable insights applies in this context as organizations need to develop a working plan on their data strategy as value erodes. Most businesses fail on data collection for AI investments and accordingly lack the edge to compete in the market.

AI is the Future of Retail and E-commerce

The traction towards AI adoption by businesses is increasing as organizations start to understand the value acquired such as superior customer experiences, forecasting and offering customized solutions. We come across AI applications in every shopping site we visit online and expect more applications in the years to come.

As innovation speeds up, estimates show a valuation of $30B in investments for e-commerce companies. Despite the slower adoption of AI in retail, we should be cognizant of the underlying challenges such as cost and lack of expertise during the implementation process. The rewards to e-commerce companies adopting AI in their operations will increase significantly as competitors catch up.

Retailers need to understand their current technological needs including data, analytics and assess areas that require urgent solutions. Preparations need to begin as the AI wave spreads across the business landscape. Lastly, enterprises must consider the quality standards of their data for them to experience the real value of AI investments.