Why are you getting into AI?

Because it has to do with your bottom line. More specifically, implemented effectively, AI can increase it.

Knowing this alone, of course, isn’t enough. What business problems are you trying to solve with AI, and how? What technological capabilities do you have at the moment, and how will they accommodate your AI activities (or not)? What data do you have? What is missing?

Technology for technology’s sake will only lead to wasted expenses. Discuss with your entire team and identify the specific objectives that AI should help you achieve. Develop metrics by which the success of the project can be tracked.

For most companies, quite a few of those goals will revolve around the customer—in particular, engaging them more effectively, understanding them more fully, and providing experiences that deliver greater growth impact.

Data. Data. Data.

AI cannot be expected to “do its magic” after being introduced to your organization. Any AI project will be a gradual process, and it can only get better over time as it learns. New products, customers, trends, and more will emerge, each changing the shape of your AI project in different ways.

Perhaps more importantly, AI will deliver nothing without the right data.

You need to use not just one source of data, but many. In fact, to get the most benefits, it is critical that you bring all the available data sources within regulatory boundaries into one place, and continuously feed such evolving to your AI models. This will be a step-by-step process, requiring technology that can accommodate such an expansive data integration effort.

There are some important questions to be asked in terms of your data. 

• What is the minimum amount of data required to not only understand your customer sufficiently but to provide them with a relevant, engaging CX?
• What data sources do you have? What don’t you have? 
• Do you have the capabilities to consolidate all the data from these sources?
• Have you mapped out a comprehensive process and acquired the necessary tools to act on the data with the help of your AI technology? 

When it comes to CX, AI is not just supposed to expedite your operations. It should ideally elevate your interactions with the customer beyond the purely transactional—by, for example, deriving their intents and optimizing communications over time. 

As consumer habits shift in the aftermath of COVID-19, you need to leverage AI-enabled insights to deliver seamless, contextual experiences across emerging digital channels.

Privacy and security

There is a fear-mongering tendency to paint the advent (or rather, further enhancement) of AI as some dystopian future coming into form. While many of those narratives are merely superficial mis-diagnoses, there is the very real worry people have about their privacy and data security.

The line between personalization and privacy invasion can be blurred easily, to the horror of your consumers, if you fail to act as a good steward of their data in not just your AI-driven efforts but all digital activities. This entails abiding by all the relevant regulations in different target regions, and never infringing on the privacy rights of your consumers.

As AI will most likely be utilized to augment your personalization capabilities, it is imperative that you can acquire a 360-degree view of the customer without compromising sensitive information. This can involve several things: a “golden record” of the customer, robust encryption and tokenization measures, rigorous access control, as well as effective audience identity management.

For more insights, watch our webinar AI and customer experience: How brands can fuse them for actual value now.