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Product Experience Strategy

Jan 17, 2024

3 min to read

Navigating AI Integration: A Strategic Approach for Retail Success

In this guest post from Akeneo partner Unifai, we give you the keys to success for implementing an AI solution within your company, while explaining how to train your teams in these new technologies to best manage your product data.

Keywords

Akeneo Community

Artificial intelligence (AI)

B2C

Retail Trends

Unifai

The adoption of Artificial Intelligence (AI) has become unavoidable for companies wishing to remain competitive and innovative. Every decision, every step of the integration process, can have a considerable impact on ultimate success. 

According to a recent study by Gartner, over 40% of companies that invested in AI technologies without a clear strategy ended up spending more than expected. So how do you take full advantage of the benefits of AI while avoiding potential pitfalls? How do you ensure a smooth transition and seamless integration?

Let’s dive into the keys to success for implementing an AI solution at home, while explaining how to find the perfect AI tool to manage your product data! 

 

Demystifying AI in Retail

Around the water cooler, you may have heard “AI is a danger, I’m about to be replaced by a robot”, or at lunchtime you’ve heard “Wait a minute, working with AI is expensive!”

Whether you’re overseeing an AI project or navigating the challenges of gaining buy-in from colleagues, breaking down misconceptions is crucial. Despite some prevalent negative opinions, AI is now a strategic pillar in various industries, from customer relations to logistics and research. It’s essential to dispel myths and showcase the diverse applications and benefits of AI in today’s business landscape.

AI offers unprecedented optimization opportunities for companies thanks to three main elements: 

  • Task automation: Using AI to perform repetitive, rule-based tasks without human intervention, ranging from simple data entry to complex business processes.This frees up valuable human resources to focus on more strategic, creative, and high-value activities. 
  • Predictive analysis: Using historical data, statistical algorithms, and machine learning techniques to identify the likelihood of future outcomes or trends.By analyzing past data, AI can predict future trends, customer behaviors, and market changes, allowing companies to make informed decisions, anticipate demand, optimize resource allocation, and proactively address challenges before they arise.
  • Pattern recognition: Using AI to identify patterns, trends, or anomalies within vast datasets that may not be apparent to human observers. AI excels at quickly and accurately recognizing patterns in data, enabling businesses to extract valuable insights. This is particularly beneficial in areas like fraud detection, customer behavior analysis, and quality control.

According to a recent Usine Digitale survey, 71% of the executives see the optimization of internal operations and processes as the main incentive for adopting AI. This trend is far from trivial, as it enables companies to increase efficiency, reduce costs, and improve the quality of their products or services. 

To take this technological revolution one step further, it’s essential to discover how to improve product data quality problems with AI, ensuring that this innovative technology is seamlessly integrated into everyday business operations.

 

Avoid Common Pitfalls When Implementing AI

Integrating AI into your business processes promises many benefits, but it also presents challenges. Let’s take a look at a few of the most common pitfalls to ensure that your organization is able to steer clear of them. 

Ignoring data security 

According to a Gartner study, 41% of organizations have already experienced an AI-related privacy breach or security incident. Selecting an AI tool with robust security protocols, data encryption, and compliance with privacy regulations is crucial for safeguarding sensitive information.

Not involving stakeholders and end users 

The engagement of stakeholders and end users from the project’s inception is vital. Understanding their needs ensures the selected AI tool aligns with expectations, delivering real added value. Effective communication and collaboration throughout the implementation process are key to successful AI adoption.

Poor communication and support

AI adoption extends beyond technology; it’s about empowering the people who use it. Gathering feedback from the team and providing necessary resources for effective tool utilization are essential. Continuous communication, feedback loops, and ongoing support contribute to a successful AI integration.

 

Steps for Optimal AI Adoption in Retail

Are you a PIM manager, ERP manager, or data manager ? Is your role to manage and optimize the quality, consistency and distribution of product information data? Then implementing an AI solution within your company is a major project requiring a methodical approach. To ensure optimal adoption, follow clearly defined steps and focus on communication.

Step 1: Assess your needs

Every company is unique. Clearly identifying your needs will help you identify the AI solutions best suited to your context.

Before adopting an AI solution, ask yourself what your real needs are:

  • How much data do you need to manage? 
  • Do you have any specific cleaning or categorization problems? 
  • What processes would you like to automate or optimize?
  • Do you need to enrich your descriptions, keywords, or titles?
  • To date, how much time do you set aside for this type of task and how much do you want to reduce it?
  • What kind of results/ROI do you expect?
  • How can AI fit into your current workflow?

By understanding your requirements, you can better understand how AI can meet your challenges.

See how Rexel improved data accuracy by 98%

Step 2: Select the right technology

Choosing the right AI solution involves aligning it with your objectives and infrastructure. Integration with existing systems, precision in meeting needs, and adaptability are crucial factors.

Opt for a platform designed to adapt and evolve with a company’s changing needs; particularly those platforms with flexible architecture and integration capabilities are ideal for companies looking to centralize the management of their product data.

To find out more : Is your product data AI ready? 

Step 3: Train and communicate with your employees 

Implementing a technology is a process, but its full adoption by teams is a transformation. Support your employees in this transition with relevant training. After all, no matter how advanced the technology, it’s only effective if it’s used properly

In addition, establish transparent communication on the benefits, changes, and support available to reassure and support your employees throughout this transition.

Anticipate reluctance, answer questions, and highlight successes to show your teams the concrete benefits of AI in their processes.

 

Harnessing AI for Growth

Artificial Intelligence is not just a technology. It is a vector of transformation for businesses. It offers incredible opportunities. Thoughtful, structured adoption of AI is a tremendous lever for growth. It’s time to embark on this adventure, armed with best practices and a clear vision. By keeping these points in mind and choosing reliable AI solutions, you can guarantee the successful and secure integration of AI into your operations.

This article is a guest post from Akeneo partner, Unifai.

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