BT Group, a major UK telecommunications company, has announced its plans to incorporate artificial intelligence (AI) into its operations as a means to improve efficiency, cut costs and enhance customer experiences.
During a recent earnings call, BT Group’s CEO, Philip Jansen, expressed optimism about the potential advantages of AI for the company. He highlighted their existing chatbot, “Amy,” which is already proficient in addressing the majority of customer inquiries. Additionally, BT Group’s exploration of generative AI, including OpenAI’s ChatGPT, could open up opportunities for the creation of innovative products and services.
Companies are widely embracing AI-powered customer service tools, including low-code and no-code solutions, to enhance their customer support capabilities. These tools utilize AI technologies to automate and improve various aspects of customer interactions. Here is a simplified explanation of low-code and no-code AI tools for customer service:
Low-code AI tools provide a platform equipped with pre-built components and functions, enabling businesses to create AI-powered customer service solutions with minimal coding. These tools feature visual interfaces and drag-and-drop functionalities, making it easier for non-technical users to develop AI-driven customer service applications. With low-code AI tools, companies can automate tasks like addressing common customer queries, delivering personalized recommendations, and directing customer inquiries to the appropriate departments.
No-code AI tools take the simplicity of low-code tools a step further. They eliminate the requirement for coding or programming knowledge, allowing users to develop AI-powered customer service solutions solely through visual interfaces. No-code tools offer ready-made templates and configurations that can be customised and integrated with existing systems. They empower business users to build chatbots, virtual assistants, and other AI-driven applications for customer service without relying on developers or IT professionals.
For instance, OpenAI’s ChatGPT is an AI language model used to create chatbots and virtual assistants for customer support.
- Google’s Dialogflow is a popular AI platform that enables the development of chatbots and virtual agents with natural language processing capabilities.
- IBM’s Watson Assistant is an AI-powered chatbot platform that helps businesses handle customer inquiries and provide personalized responses.
- Microsoft’s Azure Bot Service provides tools for building AI-powered chatbots that can be integrated into websites, messaging apps, and voice assistants.
- Salesforce’s Service Cloud Einstein uses AI to deliver intelligent customer service, automating tasks and analyzing customer interactions.
- Zendesk Answer Bot utilizes machine learning to provide automated responses and streamline customer service through help desk systems.
- Freshworks Freddy AI is an AI-powered platform offering chatbots, automated ticketing, and customer self-service features for personalized support. Ada Support is an AI chatbot platform that automates responses and provides personalised assistance using natural language processing and machine learning.
- Acquire.io is a customer engagement platform that includes AI chatbots, co-browsing, and live chat capabilities for real-time support.
- Helpshift offers AI-powered customer service solutions, such as chatbots and in-app messaging, to help small businesses provide proactive support and resolve issues across multiple channels.
Last year, BT Group’s digital unit introduced a new platform called AI Accelerator. This platform uses machine learning technology to speed up the deployment of new artificial intelligence projects. Previously, it took six months to implement these projects, but now it can be done in just six days.
One of the main advantages of the AI Accelerator is that it simplifies and speeds up the process of taking an AI project from its initial prototype stage to full production. By using common frameworks and templates, the platform reduces the administrative and technical complexities involved in implementing an AI use case.
The AI models are the key components that enable the practical use of AI. They analyse data and make predictions in ways that humans cannot. The new platform manages and speeds up the deployment of these AI models created by BT Group’s data community. It assesses their effectiveness and behaviour to extract value from the company’s massive 29-petabyte data collection.
By using common frameworks and templates, the AI Accelerator significantly reduces the administrative and technical processes involved in turning an AI idea into a fully functioning system. BT Group has also incorporated safeguards into the platform to ensure that new AI projects are evaluated according to data privacy, security, and ethics principles. This ensures that AI is used responsibly and safely across the business.
In addition to the AI Accelerator, BT Group is also embracing modular and reusable data products, which further enhance the company’s move towards becoming an AI-driven organization.
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