While artificial intelligence used to be a futuristic concept, today it has become a day-to-day reality for businesses. While the term “AI” is arguably overused and commonly misunderstood, the technology is being utilized more than ever. 

That’s not to say the actual implementation of AI is without flaws. Many technologists and digital marketers find today’s use of AI to be lacking—reasons include immature technology, tricky integration, implementation that feels invasive to the end-user, and a lack of expertise. 

Still, the majority of companies that are using AI are finding success. An international study commissioned by WP Engine and conducted by the researchers at The University of London and Vanson Bourne explored the present and near future of AI and found that 44.5% of businesses see a visible increase in sales with AI.

In the past couple of years, we’ve seen AI help out around the house by enabling home-chefs to become more creative in the kitchen and saves lives by improving medical imaging analysis to spot and diagnose cancer. But, why are some applications of AI revolutionary and others a flop? 

The potential of AI is massive but a successful AI strategy must be considerate of the increasingly privacy-conscious, fear-stricken consumer. The wrong perception of AI and its ramifications can slow the success of AI-based tools—no matter how innovative the technology. 

Approaches to AI that inspire consumer trust have the potential to deliver real value, simplifying and improving lives, products, and digital experiences. Based on our research, success with AI is contingent on the application of a set of foundational values to the key components of a digital experience—personalization, data exchange, and meaning. 

Creating Value Through Personalization: Relevance and Resonance 

There’s a lot of content out there; experiences that are memorable have roots in personalization. But personalization is more than just including first names in email introductions, it needs to be both relevant to the consumers’ immediate and long-term needs as well as resonant with your business’ core values. By incorporating intention into AI and personalization, you can create experiences that your customers want to engage with and join. 

Part of creating personalized experiences is gathering the intel you need to tailor specific experiences to specific audiences. Sensitivity, transparency, and diligence need to be fundamental principles of your strategy to collect and manage personal information. 

To learn more about using relevance, resonance, accuracy, and intent to guide your personalization strategy, check out the full study

Creating Value Through Data Exchange: Honesty and Trust

Most organizations have a surplus of data. But businesses need to be tactical about the way they use data to solve problems. Having the right data to inform your AI strategy isn’t always straightforward—the process involves cleaning, preparing, and getting the data ready to be fed to an AI or machine learning platform. However, if companies can successfully pinpoint a problem, parse the data, and feed it into a self-improving AI system, the results are invaluable. 

Our survey shows that among businesses that have adopted an AI strategy, 41% said they saw an increase in sales revenue, 40% saw in increase in website visitors, and 38.7% saw an increase in customer satisfaction.

Businesses must take continuous steps to protect and respect the data of their customers; companies interested in AI will tread the line between the practical benefits of an AI-powered web, and the ethical implications of collecting and using the data that fuels it. 

Consumers know data is a precious commodity and expect to receive high value in exchange for the data they provide. In order for consumers to offer up that information, companies must build trust and honesty by establishing a data collection and AI strategy that aligns with their current ethical policies, their organizational values, and the type of company they aspire to be.

To learn more about what high-value experiences consumers expect in exchange for their data, check out our full study.

Creating Value Through Meaning: Fairness and Diversity 

The process of collecting accurate data and using it to fuel AI systems is not enough to create meaningful interactions. Creating breakthrough digital experiences is about more than a specific reaction with a customer—it’s about emotional resonance. When businesses are able to create a feeling that taps into a person’s interests, enjoyment, and sense of belonging or achievement, they will be able to build a loyal following. That’s the true potential of AI. 

The values driving meaningful experiences for AI are fairness and diversity. Successful implementation of AI will support the human desire for connectedness and belonging. Creating meaningful and ethical experiences is only half of the equation; companies must work hard to spot and eradicate biases in AI applications. Avoiding biases in AI has to be a proactive process. Data needs to be continually monitored for unfavorable patterns. 

By combining the above values with the implementation of AI, businesses can take their digital strategy to a new level. By appropriately incorporating the values and ethics of personalization, data exchange, and meaning into AI systems, consumers will undoubtedly enjoy more powerful digital experiences and a more positive customer journey overall.