AI in the service of a positive and privacy-respecting customer experience

Artificial intelligence is on the rise and the next few years will see real benefits for businesses and the way they work.

Many discussions about the possibilities proposed by AI have begun to bear fruit. We are at a technology juncture where companies are considering implementing these solutions to automate machine learning (ML) pipelines and deploy multi-tenants for thousands of IoT devices.

Developers and engineers now have tools that allow companies to go from proof of concept to real ROI.

One-click installation of AI?

Currently, the high cost of hiring AI researchers and engineers is crippling the business. On the other hand, the sophistication of no-code / low-code tools and solutions that will be on the market in the next 12-24 months can help them set up solutions at home, with just a few clicks.

This is proof that companies are expanding and simplifying the market, enabling anyone to create and deploy their own AI systems, whether in cloud, edge, mobile or hybrid mode.

This democratization of the design and deployment of AI solutions has brought many benefits to companies, opened up opportunities for innovation and, more importantly, provided an equal playing field for all companies.

Having the maximum number of hands soon, these tools will help companies to increase their knowledge and / or skills to acquire skills, thanks to automation. In addition, customers will benefit from personalized recommendations and a feature-rich experience.

AI that respects customer privacy

Consumers are increasingly concerned about the personal data they share. In other words, companies need to explore new ways to leverage their customers’ behavioral data. They should consider running their own algorithms to engage their customers more (for example, retail).

There seems to be a stigma attached to AI and data protection. But, when applied properly, AI is in a very good position to improve data security across all industries.

It all depends on how it is implemented. Take the example of an AI system aimed at preventing damage to automatic checkout. The system will monitor customer behavior to see if they are releasing product tickets to pay lower prices for more expensive products. For example, one could take a ticket out of a serial box and put it on a Bluetooth speaker, paying a few dollars for the speaker when the price is too high.

The system monitors in real time and alerts the seller whenever a problem arises. The customer is then challenged and allowed to correct the error. Installed in self-service checkouts, the system monitors, detects and warns without recording any faces. He made a decision and immediately informed the staff. With the rise of IoT devices and the processing of AI algorithms across the network, companies are relying on data to make better business decisions in real time. All other raw data will be deleted. All of this, combined with regulations such as GDPR, makes it easier for engineers and researchers to create effective systems to protect human privacy and increase business profits.

Where is the AI ​​drive profit?

There are two main areas where AI can help you gain. The first is to target your customers with personalized content or products. The second is to provide customers with a feature-rich experience.

For example, companies can measure customer behavior through an “comparison and prediction” method using algorithms that allow customers to discover products they did not need or even discover content that interests them.

Consumer burden has always been a sacred grill for business. Being able to accurately predict the products they want helps increase profits and loyalty Measuring customer behavior has become a challenge, but because of the problem of sharing personal data (see above), this problem can be solved.

The second goal is to create a rich experience for customers and improve business skills using a variety of AI tools. It can answer questions quickly and efficiently using an AI chatbot, or auto-tag photos and videos to drive higher engagement. In this way, experiences become richer in features and more affordable.

Ultimately, a business wants to improve its bottom line by selling more products or acquiring skills. Businesses need to start by asking what their goals are and using the tools available to achieve them.

Improving efficiency by delivering work in real time to the store using Reinforcement Learning or product identification using multiple deep learning models. Moving from AI and ML research to production is key to increasing ROI and improving customer experience.

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