Artificial Intelligence (AI) is a very popular buzzword in the retail industry today, and not without its merits. As such, it is important to know the misconceptions that are out there and what the truth really is.
Beware of AI misconceptions by being prepared.
Like with anything else there is a right way and a wrong way to approach and implement AI and advanced analytics technologies.
Approaching AI and analytics the wrong way by believing misconceptions can be costly, time consuming, and detrimental to your business. Retailers who jump in unprepared can spend a year integrating a software solution into their existing infrastructure just to have it fail or not solve the challenges they were facing in the first place.
However, if you’re able to steer clear of these misconceptions, AI can be a very profitable investment. In fact, according to a recent McKinsey report, leading retailers investing into advanced analytics, such as inventory optimization software, have been outperforming their competition by 68% in the past several years.
So, what are they doing right and what misconceptions should you avoid?
Misconception 1: AI has one agreed upon definition.
Often people will hear the term AI in a particular context and assume that the meaning they understood holds true in every scenario.
In truth: AI is an umbrella term that defines a wide variety of processes. Some of these processes include data analytics, predictive analytics, statistical methods of analysis, different types of machine learning, and more. It is important to understand that AI is not a magic solution for all of your problems.
How to get it right
- To successfully implement AI it is integral to thoroughly understand what problem you are trying to solve.
- You need to thoroughly vet the vendor who is selling you an AI Solution. Ask questions like:
- What does it do?
- How does it work?
- How does it really differ from all the other solutions?
- Understand that to solve your problem you will need to use multiple forms of AI that will together develop a solution.
Misconception 2: AI Can Solve All Your Problems.
Many Retailers believe that AI is a one-size-fits-all solution that can be easily translated from one business to the next.
In truth: AI can be a very useful tool if used correctly. An AI solution must be curated to the business, and even more specifically to the problem within the business. Every retailer is unique and has their own specific challenges, attributes, requirements, and internal structure.
How to get it right?
- Make sure that the AI solution is Retail specific. Buying an AI solution that works for healthcare, banking, or investment is like buying a vacuum cleaner that also brews coffee.
- Your AI solution needs to be one part of a common analytics platform that will take into consideration a variety of factors in your business.
- The Analytics platform that you are using should be able to create new business rules and exceptions so that it can effectively incorporate the AI solution.
Misconception 3: All AI Solutions are Approximately the Same.
Many people believe that because the technology has been developed, all AI providers have the same knowledge and understanding of AI and so can provide comparable service.
In truth: Providers vary widely not only in their understanding of AI technology, but in the way they have developed their solutions and technology. Companies that claim to “do AI” are often leaning on the term because it is a buzzword and can be defined to mean whatever is most convenient for them.
How to get it right?
When Vetting a vendor that will provide AI solutions be on the lookout for:
- Companies that provide a ‘shinny product’. That is, a basic data mining and statistical analytics software that has a nice-looking dashboard and no unique computational technology.
- Companies that provide a general Ai solution that covers many industries. Make sure it is retail specific. (Think Coffee maker, not vacuum).
- Companies that have retail specific testimonials (preferably from leading retailers).
Misconception 4: AI is a Ready to Use Solution
Retailers often think that they can buy an AI solution, and start using it the same day.
In truth: A retailer needs to be ‘AI Ready”. This is one of the most unforeseen challenges when implementing any AI solution. Once you have decided what is the problem you are planning on leveraging Ai in order to solve it, you need to make sure you have infrastructure in place to implement the AI solution.
How to get it right?
Before you purchase and implement an AI solution, make sure your business is ready by asking the following questions:
- Is your data thorough and clean so that an AI solution can effectively use it? You should have at least:
- 2 years of sales history
- 1 year of promotions
- Product hierarchy
- Any data that is relevant to your specific retail organization.
- Do you have a plan for introducing AI in your business?
- How will you integrate the AI solution with your current technology ecosystem?
Misconception 5: AI is a con
After reading this article you may think that all vendors selling you AI solutions are trying to use buzzwords to sell you simple surface level analytics software that uses statistics and flashy graphics. Or perhaps you have decided that AI cannot work for your business because it will take too much money and time to effectively implement a solution.
In truth: AI can be a very valuable tool that can solve a number of real challenges faced by many retailers today.
How do I get right?
- Don’t rush into it.
- Get your data ready and know what specific problem you need to solve.
- Decide which specific tool would be applicable for your situation.
- Properly vet vendors to make sure that their solution is specific to retail and to your problem.
- Have a plan for how you will integrate the AI tools into your existing infrastructure.
Yes there are effective and retail specific AI and advanced analytics tools that you can use, visit Retalon.com to see a variety of AI tools and read about how they work and what they can do for your business.
About the Author:
Alina Sayapov is the Content and Communications Specialist at Retalon. Since 2002, Retalon has optimized pricing, inventory management, merchandising, planning, procurement, and marketing operations for retail organizations in a variety of industries. Retalon products range from task-oriented solutions to a common analytic platform, resulting in tangible optimization of the supply chain and significant measurable benefits for the entire organization. Visit www.retalon.com to learn more.