AI at work: How AI could optimise enterprise-client interaction

BBD, 20 /08/ 2024

Collected at: https://www.itweb.co.za/article/ai-at-work-how-ai-could-optimise-enterprise-client-interaction/KzQenqjyLrVMZd2r

Artificial intelligence (AI) has become a crucial element in transforming business operations and optimising internal processes. Generative AI, which makes use of large language models (LLMs), have truly taken the world by storm in their ability to hold conversations and generate human-quality text. With this potential lying in wait, many businesses are grappling with how to operationalise and harness this capability to elevate their client service offerings. “This type of technology, applied correctly, will optimise the way enterprises interact with their clients,” explains BBD executive, Streicher Stegmann.

Transforming client interactions

Imagine a virtual assistant that understands you as a client, and can proactively provide relevant suggestions or solutions – one that will start your journey off with exactly the information you’re looking for – meeting you right at your need. By analysing vast amounts of data using data science and machine learning models, organisations can build unique profiles of each client, understanding their past interactions, preferences and current needs, which can be used by these virtual assistants to deliver personalised answers. This empowers businesses to deliver tailored responses, information and recommendations, fostering a more satisfying client journey.

One of the least risky approaches to incorporating LLMs into enterprise operations is using them as AI agents and assistants (we touch on this topic here). This application is particularly effective for internal processes and efficiencies, handling repetitive and mundane tasks and performing analytical searches across organisational data in a more meaningful manner.

One such approach is in an assistant capability, where AI can provide agents with real-time, personalised information and recommendations during client interactions. This can significantly enhance the efficiency and effectiveness of human agents, allowing them to dedicate more time to complex issues while providing world-class client services.

Reaping the rewards

“Personalised client interactions and reduced handling times are key advantages of integrating AI into enterprise solutions,” explains Angelo Camacho, BBD executive. “Such a solution doesn’t look to replace human agents, but rather to empower them by automating routine tasks, allowing them to focus on solving more complex queries and building stronger client relationships.”

Some of the key benefits of leveraging this technology include:

• Personalised responses: LLMs can make sense of and interpret structured data to deliver personalise client interactions through a virtual assistant to tailor responses and information to each client’s unique needs.
• Improved agent efficiency: AI can assist in deflecting simpler inquiries, freeing human agents to handle more intricate client issues. This can lead to faster resolution times and improved overall client satisfaction.
• Data-driven insights: AI can uncover hidden patterns within large datasets, providing valuable insights that can be used to deeply personalise client interactions.

Understanding the risks

While AI offers exciting possibilities, on the other side of the coin there are challenges associated with implementation. One key concern is ensuring the accuracy of information provided by AI systems.

These include:

• Prone to hallucination: Since LLMs are generative models trained on massive datasets, careful consideration needs to be given to potential biases or factual inaccuracies within the data. “Generative AI can’t perceive whether the information it is presenting is factual or not,” cautions Camacho, “which means that by exposing generative capability in a chatbot, we are exposing the organisation to risk.” As a result, most companies use these capabilities internally to avoid risks, ensuring safe usage rather than risking exposure to their customers.
• Grapples with domain-specific datasets: One of the key areas that BBD has been focusing on is how to use LLMs in the context of enterprises with domain-specific data: “LLMs are great at general conversation based on their training datasets,” says Camacho, “but they’re not very good with a specific enterprise’s domain-specific datasets, and that’s a problem that we’ve been working to solve.”

The future of AI in client service

While the path to fully utilising generative AI for client service is ongoing, one thing remains certain: LLMs are the future for how enterprises will interact with and service their clients. By focusing on practical applications and addressing the real-world challenges of integrating AI into enterprise systems, BBD aims to lead the way in leveraging AI for enhanced client servicing and operational efficiency. BBD’s commitment to innovation, combined with our growing understanding of AI technologies, positions us as a trusted partner for organisations looking to navigate the complexities of the AI ecosystem. “To date,” explains Stegmann, “BBD has begun working with key clients to implement and operationalise AI-driven solutions. It’s these types of cutting-edge solutions that we believe will be crucial in keeping our clients relevant and applicable.”

Interested in leveraging LLMs and generative AI for client servicing? Click here for a short video on where to start, with BBD CEO Kevin Staples, or get in touch with us today.