Impacts And Limits Of Artificial Intelligence In B2B E-commerce

If Artificial intelligence offers considerable advantages for e-commerce, it also has its limits and involves specific challenges that it is better to keep in mind …

Artificial intelligence plays a crucial role in digital transformation plans, and it powers search engines, virtual assistants, and product recommendations.

For B2B e-commerce professionals, Artificial Intelligence can represent a real competitive advantage. But AI has its challenges and limitations, and its implementation can be expensive, which leads B2B companies to wonder if there are alternatives …

The Limits Of AI In Commerce

Artificial intelligence applies a model or algorithm to process large amounts of data and predict future outcomes.

Although it is very sophisticated, it needs to be personalized and tested to perform as expected.

Artificial intelligence doesn’t work in isolation, and it is connected to existing tools, platforms, and processes. Its implementation can be expensive and somewhat uncertain. 

First Limit: Identify Realistic Use Cases

Over 65% of B2B buyers will likely switch suppliers if they don’t offer a personalized experience.

In this sense, the most popular AI use cases in B2B e-commerce focus on UX. Other things best managed by AI include product recommendations or sentiment analysis.

For example, Amazon has invested heavily in its AI-powered recommendation engine to understand customers every step of the way.

Amazon Personalize reviews previous purchases to optimize the algorithm to provide better product recommendations. The key to Amazon’s success is its commitment to creating the most personalized customer experience.

Second Limit: Putting The Data In Order

According to an O’Reilly report, 15-20% of AI designers cite missing or inconsistent data issues.

The data requires analysis and preparation before the algorithm can use it.

Human intervention during preparation can then lead to errors before the AI ​​processes the data.

Third Limit: Set Up Teams Specializing In Artificial Intelligence

AI requires a team of BI professionals, engineers, and analysts to maintain it properly.

Unfortunately, AI professionals are hard to find. The talent gap in the AI ​​industry affects all skill and experience levels.

Fourth Limit: Culture And Risk Management

AI is still a relatively new technology, and everyone has a different idea of ​​what it is and what it can do for a business.

To have the best chance of success, it is crucial to integrate all stakeholders in your AI strategy and involve them in defining the objectives. Complete visibility leads to the most excellent chance of success. 

Alternatives To Artificial Intelligence

However, not all businesses need AI, and other alternatives can be deployed.

For many e-commerce functions, a rules-based workflow automation engine can deliver the same results at a reduced cost.

For example, a product recommendation algorithm might not need AI or a personalized quote or payment process.

The Automated Workflow

Automated workflows and AI involve relying on well-performing IT infrastructures to perform tasks. 

AI is the best choice for evaluating several unknowns, such as fluctuations in demand and advance purchases.

For example, Amazon is well known for using algorithms to strategically place items in warehouses closest to customers before adding those items to their cart.

These systems anticipate individual tastes and seasonal, weather, and traffic conditions to deliver products as quickly as possible.

Yet, AI is not needed to identify the best warehouse to ship products.

An automated workflow can route orders to the warehouse closest to the customer, creating the same experience Amazon offers with AI.

In this case, an automated workflow can be implemented faster and costs much less.

Automated workflows can be the ideal solution for repetitive tasks or involving data manipulation.

Make Sure The Artificial Intelligence ​​Works For Its Needs

Any AI solution must deliver value that exceeds the costs of administering data and building a dedicated team.

Let’s not forget that AI can present a multitude of challenges. Therefore, you must ensure that you have a valid use case and the resources to invest in carrying out your project.

Considering these elements, alternatives such as automated workflows are a good option.

Finally, it is essential to remember that the simplest solution is often the best .

Also Read: Artificial Intelligence & cybersecurity: A Curse And A Blessing At The Same Time