The future of AI: Where AI is Headed and How it Will Impact CX
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The future of AI: Where AI is Headed and How it Will Impact CX

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Sofía Hanna By Sofía Hanna | Journalist and Industry Analyst - Wed, 05/03/2023 - 17:32

Artificial intelligence (AI) is benefiting many business areas, especially customer experience (CX). AI has made significant advances in the past 70 years, which have enabled businesses to deliver more personalized experiences to their customers, improve their operational efficiency and ultimately drive growth. While its potential is enormous, its use can also bring significant risks.

In the future, AI may be able to automate up to 70% of the tasks that humans perform today. AI can free up resources, allowing humans to focus on more complex tasks. For example, in the healthcare industry, AI is used to help diagnose and treat patients, while in finance it is used to analyze financial data and predict market trends. “Automation is not meant to replace humans. It should make their work easier,” says Isaac Solís, Pre-Sales Director, Zendesk. 

Companies can use Zendesk's AI solutions to make their CX teams more efficient. Advanced bots with pre-trained customer intents provide personalized and accurate responses, while intelligent routing helps prioritize and automatically direct conversations to the right agent. Contextual information and AI-powered macro suggestions also improve agent effectiveness.

For example, Zendesk’s Agent Workspace reads a client's request or history and uses AI to summarize the issue, regardless of the channel used. It later provides the summary to a support representative who then takes over. Additionally, the AI can offer suggestions to help solve the problem. “This is the part that excites me the most, the AI can even offer suggestions based on the tone and intention identified in the user’s requests,” says Solís.

AI has become more accessible thanks to the development of Language Models (LM) that also use synthetic data, which is real data that has already been analyzed by humans, explains Solís. According to Gartner, 60% of data used by AI will be based on synthetic data by 2024.

While the potential benefits of AI are vast, there are also significant risks associated with its use. One of the main concerns is that AI systems may not fully understand the unique nuances of a particular business or industry, leading to incorrect or misguided decisions. Additionally, AI systems are not infallible and are prone to making errors, especially when they are used in complex or unpredictable situations. Another major risk is that AI can be manipulated or used to deceive individuals or organizations.

Solís suggests three key strategies to mitigate the risks associated with the use of AI to address customer issues. The first is to adjust and base the AI on real facts, while adjusting the parameters of the AI according to the appropriate data. "On what facts should I base my AI to serve our users? In the data of my product and industry, it is not necessary to add external data beyond what is needed for its work,” says Solís. 

The second is to keep humans informed. "AIs make mistakes, it's important to have expert eyes to monitor responses that are not plausible,” says Solís. Finally, the third strategy is to reduce the scope of responses and scale as needed. "It is not necessary to leave the AI to solve problems; it is important to identify when the situation should be moved to a human for proper handling," he adds.

To effectively supervise AI and mitigate the risks associated with its use, businesses must adopt a proactive approach. “AIs do not have a moral compass; they are based on language, therefore human intervention is always necessary,” says Solís.

This involves adjusting AI systems to follow facts and data, rather than assumptions or biases. Additionally, companies must keep humans informed about the decisions being made by AI systems. Humans should also be provided with the tools they need to monitor and evaluate AI performance. One way to achieve this is by reducing the scope of automated responses and escalating them to human operators who can intervene if necessary.

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