“Garbage In, Garbage Out”
The Risks of Over-Reliance on AI in Customer Service
AI technologies, like Agent Assist and real-time artificial intelligence, have been game changers for boosting customer service satisfaction.
They promise optimized workflow automation, happier agents, and intelligent conversation analysis within the contact center.
However, AI is only as good as the information you feed it.
Maintaining the quality of AI’s inputs and checking its outputs is a human task.
As the saying goes, "garbage in, garbage out." Understanding this principle is crucial for anyone who wants to harness the power of AI without falling into the pitfalls of misinformation and ineffective automation.
What does “garbage in, garbage out” mean in the context of AI?
The term "garbage in, garbage out" in the context of AI refers to the principle that the quality of output is determined by the quality of the input. AI tools, including machine learning models, are only as good as the data and instructions you provide them. While AI can significantly improve various aspects of customer service, it can't independently know which questions to ask your customers or which data files need to be fed into the system for accurate analysis. Enter you. The human.
Your CRM is critical to maintaining healthy data. It’s absolutely vital to make sure that you feed your CRM the right data because once bad data is in there, the knock-on effects can have far-reaching consequences for anyone relying on that data. Unfortunately, as organizations grow, data quality often suffers, and data stewardship tends to get overlooked in growing businesses.
To be ready to use any AI tool effectively in your organization, you need to have accurate and well-structured data. Start with your CRM.
“While attending the Salesforce AI Day in London in late June they specifically covered this topic and talked about how while they may have AI based tools ready for their customers to use, the customers themselves may not yet be in a position to use them." -Brendan Jackson, COO, Deepdesk
What is real-time artificial intelligence?
Real-time artificial intelligence refers to AI systems that can analyze and act upon data instantly. This immediate response time is particularly beneficial in a customer service environment where quick resolutions are key to customer service satisfaction.
However, if the input data or parameters are flawed or irrelevant, the real-time suggestions or actions could misguide your agents, affecting the quality of service adversely.
What is a machine learning model?
A machine learning model is a form of AI that is trained to make decisions or predictions based on the data it has been given.
While machine learning models excel at pattern recognition and predictive analytics, they are not immune to the "garbage in, garbage out" principle.
For instance, if a machine learning model is trained on outdated or biased data, its predictions or suggestions could be equally flawed. Take chatGPT for example. The model was trained based on data up to 2021. So, when it comes to world events, or knowledge after that period, it can’t offer you a good, truthful answer.
What is agent assist?
Agent Assist is an AI tool designed to help customer service agents by offering real-time response suggestions, among other features.
However, it's crucial to remember that while Agent Assist can make a new "digital" agent effective more quickly, the quality of its assistance is wholly dependent on the quality of its training data and pre-configured responses.
Conversation intelligence for contact centers
Conversation intelligence can analyze and improve the quality of interactions within a contact center by providing real-time insights and post-interaction analytics. But again, the system needs to be trained on high-quality, relevant conversations to offer any genuine insights that can improve customer service satisfaction.
Training new agents and rolling out new services
AI is particularly beneficial when you have new agents or when you're launching new products or services. For example, when a new cell phone plan is released, AI can be programmed with answers to potential customer questions. However, if those programmed answers are inaccurate or unclear, it could lead to a host of problems, from unhappy customers to misinformed agents.
Balancing AI with human oversight
While AI offers valuable tools for improving workflow automation, conversation intelligence, and overall customer service satisfaction, it's crucial to balance these tools with human oversight. Staff should be trained to scrutinize AI suggestions critically, and managers should frequently review and adjust AI settings to ensure that they align with the company's current policies, products, and services.
Tools like your CRM, which are used broadly throughout your organization, are vulnerable to data quality issues from careless inputs. It’s important to educate everyone who uses your CRM and other database tools about the importance of data quality control and how human oversight in this area can lead AI outputs astray.
Customer service software: a tool, not a solution
Remember that customer service software equipped with AI capabilities should be viewed as a tool rather than an all-encompassing solution. The technology can undoubtedly aid in making agents happy and efficient but only if paired with high-quality data and ongoing human oversight.
While AI presents promising opportunities for improving customer service, the "garbage in, garbage out" principle serves as a vital cautionary note. As AI systems are inherently limited by the quality of their input, businesses must ensure they feed these tools accurate, high-quality data. For best results, businesses should be aware of maintaining data quality from first touch to database query. Your CRM is a key part of this equation, so be sure anyone using it understands the role CRM best practices play in feeding AI the right data.
Coupled with ongoing human oversight, AI can then genuinely be a force multiplier in your quest for superior customer service satisfaction. This will always start and end with the human element.