Energy is precious, and the human brain is wired to conserve it as much as possible. The Law of Least Effort suggests that people inherently seek the most straightforward route to achieve their goals or solve problems. Whether in problem-solving or daily decision-making, individuals are inclined to conserve mental and physical resources by opting for the least-demanding course of action.
This concept reflects the human tendency to minimize effort and streamline tasks. Throughout history, inventions that simplify tasks and reduce effort have gained widespread adoption. For example, the printing press made it easier to share knowledge, phones made it easier to communicate with people, and Uber made it easier to get around. Generative artificial intelligence is the next big technology streamlining how we operate.
As customer expectations continue to rise, contact centers require additional resources to meet these demands. GenAI is playing a pivotal role in facilitating seamless data interaction for contact centers, simplifying the process for agents to address customer issues and provide data-driven recommendations. Integrating genAI in call centers can significantly enhance efficiency and customer satisfaction, but only if you do it right. Here are four considerations and best practices when choosing a genAI vendor:
- Choose industry-specific solutions: Opt for AI solutions designed for your industry. Industry-specific AI models are trained on domain-specific data, making them more capable of understanding and responding to industry-specific issues and customer inquiries. Also, it's a bonus if the vendor you're considering deeply understands your industry because this can make or break a client-vendor relationship.
- Prioritize data quality over quantity: Focus on data quality rather than just the quantity of data. High-quality, well-labeled data will result in better AI performance. Make sure your vendor can help you gather the right data and refine it in a way that results in accurate and meaningful answers. Mature solutions will typically incorporate a human-in-the-loop approach to data, where they gather knowledge from a company's top talent and refine that data to supplement their dataset and enhance the model's intelligence.
- Include continuous learning capabilities: Choose a solution that has continuous learning capabilities built in. This ensures the AI engine adapts to evolving data patterns over time, improving its accuracy and relevance. Additionally, this means the engine will become smarter over time as users conduct more customer interactions using the engine. This accumulation of knowledge allows the user to learn from a broad spectrum of solutions, leading to ongoing improvement.
- Don't forget about data security and privacy: Ensure that your AI vendor has robust data security and privacy measures in place. If your vendor integrates a large language model like OpenAI's ChatGPT, ensure they have a strong firewall and data protection infrastructure. Security breaches can be costly and damaging to your reputation.
It's clear that genAI is here to stay, and, given the current pace of innovation, its advancement is inevitable. The value it can bring to contact centers is undeniable, and I firmly believe it is the future of how contact center workers and others in the service industry will interact with data. Traditionally, individuals have interacted with data through dashboards, however, the majority of people don't want to or have the skills to interact with data in that way. GenAI not only equips individuals with crucial data-driven skills but also stands as the catalyst for substantial organizational transformation in contact centers, promising meaningful improvements in customer experience.
Shahar Chen is co-founder and CEO of Aquant.