Artificial intelligence is here to stay, and the reason is simple: a proven return on investment.
Companies in many sectors are incorporating artificial intelligence because the rise is tangible. According to an Accenture report, the implementation of artificial intelligence solutions has helped increase profitability by 38% on average in 16 sectors. For the entire US economy, this stimulus could generate an additional gross value added of $ 14 trillion by 2035.
AI offers businesses more than just a gradual improvement; it is a transformative technology. By using AI to automate repetitive and time-consuming tasks, you can free valuable human resources for higher value work. Artificial intelligence also improves lead generation processes, marketing and product development workflow, resulting in more innovative products and a better customer experience.
Artificial intelligence will become an essential part of the customer experience as traditional methods of customer segmentation become less and less efficient. By using AI, companies will be able to evolve while creating more personalized experiences, such as custom incentives or rewards based on current location services, which quickly become the expectations of their customers.
But even the most revolutionary technology will be of no use if no one can use it, and the user experience is often the limiting factor for a successful implementation of the AI.
Users are left behind
Artificial intelligence is an emerging technology with a lot of experimentation still going on. Many companies are trying to set standards as they go, using their customers as lab rats. These companies often lack a clear vision of how individuals or companies will use their product. Even worse, they do not recognize the problem. According to Capgemini, 75% of companies consider themselves to be customer-centric, but only 30% of consumers share this point of view.
Companies learn that the technology they invest in does not automatically create a good user experience. Take conversation assistants at home, for example. An IDC report predicts that the adoption of cognitive systems mimicking the human brain, like the systems used in virtual assistants, will increase the AI's revenue by $ 8 billion. in 2016 to more than 47 billion in 2020. In the race to create the next VUI voice user interface, companies have invested less in the user experience, thinking that it would be easier to design because there is no visual component.
In reality, virtual user interfaces are harder to design for the same reason: wizards are currently overly dependent on a specific set of voice commands, pronunciation, and syntax. A Nielsen Norman group usability study found that conversation assistants were "almost useless for even slightly complex interactions".
In a number of sectors, companies are striving to generate revenue from this emerging technology, creating complex interactions for consumers. From strategic intelligence scorecards to your smartphone, each new technology brings a learning curve to users. But AI often works so fast and so dramatically that it causes widespread problems on the consumer side that technical teams never anticipate.
To lack confidence
AI only works with continuous data feeding, and it has been shown that data introduces various demographic bias into the models. For example, if this data breaks consumer confidence (for example, if a route-sharing algorithm drives drivers away from certain parts of the city or distributes concerts to drivers in an unbalanced way), the relationship can be difficult to repair. Customers value human qualities such as morality and fairness, but artificial intelligence algorithms are not always effective. When Microsoft deployed a conversational chat powered by real-time artificial intelligence on Twitter, for example, the bot was almost immediately corrupted by trolls. AI bias is a big enough problem that Google has even created a tool to test it.
As evidenced by numerous breaches of security (Best Buy) and breaches of privacy (Facebook), companies forget that trust is part of the customer experience. Customers are reluctant to work with companies that do not explain how they handle user data. It is easy to understand why only 20% of consumers "trust" organizations to keep user data confidential, while 78% of respondents say data confidentiality is "extremely important" for them. Trust is part of the customer experience and, if AI can not win that trust, businesses are less likely to become truly loyal.
That's why companies that are interested in the customer experience when they join AI have the opportunity to get ahead of their competitors. While those in the industry are aware of the internal benefits offered by AI and data automation for some time, mainstream consumers are just beginning to recognize the potential of AI. to improve their daily lives. Companies that focus on the user experience in their artificial intelligence products have the most to gain in the coming years.
Cure the ills of AI
To create a better user experience, product teams must operate at least three key areas with an AI product.
1. Focus on ease of use
If customers need a machine diploma to learn how to use an AI product, there is a problem. The artificial intelligence must allow to win quickly and be easy for users to understand. It is also important that products have few barriers to entry to encourage their usual use. As standards are established, more complexity can be introduced. (This applies for example to VUIs, as well as to Business Intelligence dashboards and other AI outputs.) If you need to, first create products with immediate value, then consider a different business model for more advanced features when customers know you can deliver what you promise.
2. Prove that customers can trust you
Customers want to know that their data will never be compromised or misused, and a good customer experience will help you communicate that. Reliability and constant availability are also essential to win the trust of consumers: if you want customers to believe in your product, it must be available at all times, but without compromising privacy (for example, virtual user interfaces that listen only a few seconds at a time). A better customer experience is the first step to gaining trust, and this type of relationship will help energize the business outside of traditional marketing channels.
3. Eliminate possible biases
Make sure that artificial intelligence does not generate data excluding important areas of your target audience by introducing bias into the model. AI systems are designed to identify models and can correlate the inputs of the results. So be sure to take into account and test the limits of AI. Know the limits of system abuse that can lead to unexpected or unwanted outputs. Remember that AI can not distinguish right from wrong or truth from lies. That's why people start to worry about the information they receive from Facebook's personalized news feed algorithm.
With so many potential benefits and huge opportunities in the field of artificial intelligence, it's easy for companies to forget about the modest users, especially when they're trying to justify an investment in technology. But the customer experience is what will eventually separate successful artificial intelligence projects from those that fail. Even if their projects are not as bright, the technical teams capable of providing an easy-to-use and easy-to-trust product will ultimately be the ones that will make the most of their AI investment.