GenAI has revolutionised the way businesses operate, including the ability to target brand experiences and customer communications.
There is no doubt that AI is unlocking capabilities previously out of reach for businesses across various industries, from start-ups to retailers and financial institutions, and levelling the playing field.
According to “IDC FutureScape: Worldwide Future of Customer Experience 2024 Predictions — Asia/Pacific (Excluding Japan) Implications”, a third of customer communications will be supported by real-time updates enabled by AI by 2026.
Another study from IDC found that 39% of businesses in the Asia Pacific region view conversational AI as a critical investment priority over the next two years.
In an email interview, Akarat Ngandee, Head of New Business, APAC, Infobip, shared insights into this AI trend.
How is AI creating a level playing field, giving businesses access to capabilities including skillsets that were not possible before?
Akarat Ngandee (AN): With the momentum strong around AI, some businesses are finding they are facing stronger competition and a risk of disappearing into the crowd because more around them are using AI or at least have started on that journey. But it is also an opportunity for them to stand out.
With AI’s potential extending far beyond just automation, it is becoming powerful driver of efficiency, productivity, and profitability. By streamlining repetitive tasks, AI is freeing up valuable human time for more meaningful work and critical thinking. It can manage multiple tasks at the same time, allowing businesses to achieve more in less time. This productivity gain is empowering businesses to operate with greater efficiency.
What is particularly impressive is AI’s impact on decision-making. It is giving us the ability to facilitate the analysis and interpretation of vast amounts of data quickly to make more informed choices. By making full use of real-time insights brings a competitive edge to businesses, we are seeing smarter decisions based on data-driven evidence rather than just intuition. AI offers scale, especially when tailored to the specific needs of businesses of all sizes and across diverse industries such as banking, retail, and everything in between.
How can businesses transform ‘owned’ data into actionable intelligence?
AN: If we understand that intelligence is giving businesses the ability to effectively meet the evolving preferences of consumers and business needs, this intelligence stems from what we call “datafication” – the process of converting various aspects of our lives, activities, practices, and social actions into digital data. When properly analysed, this intelligence can help businesses make more informed decisions, improve customer experience, optimize supply chains, develop products and services and more.
For businesses to move towards this intelligence creation, they will need to adopt these three principles:
- Identify the intelligence needed aligned to the business priorities. For example, business decisions such as expansion into new geographies, focusing on new customer segments, or growing customer loyalty of an existing base can be greatly refined with better data.
- Make sure data is ‘good data’. Quality and accurate data helps train machine learning (ML) foundation models to make informed decisions, but the starting point of robust data that is managed appropriately is critical.
- With humans in the loop, talent must be skilled in that role and more. Create an AI skills and knowledge program that carefully identifies who needs additional training in what knowledge and expertise.
When following these, datafication can be a driver for sustainable success, empowering businesses to make informed decisions that truly connect with their evolving audiences. This also means remaining agile and adaptable, anticipating what is coming next and proactively adjusting products, services, and more to always stay ahead.
What industries are reaping the benefits of AI?
AN: One of the first ways we are interacting with AI and seeing rapid change is in the context of customer experience, where it is transforming the way consumers interact with businesses.
The banking and finance industry has always been known for its conservative approach to operations, but it is now undergoing a big change with AI. With retail banks deploying conversational AI, they can better handle increasingly complex customer inquiries, making it easier for banks to provide 24/7 support that easily rivals human agents as well as completing tasks within a shorter period. For example, by integrating data on historical product and services information, and past customer service interactions, AI can improve targeting and personalization like never before.
AI also brings value to retail and e-commerce as more consumers turn to the convenience of online shopping. By bringing conversational AI to chatbots on your customers’ favourite channels, they can easily browse products, place orders, make payments, and get support, all in one place. For businesses, using AI not only streamlines operations and boosts efficiency but also enhances the overall customer experience.
Whilst these sectors are already adopting widely, this will extend into industries that are also heavily reliant on human involvement such as education. In these fields, we anticipate the integration of a blend of AI capabilities like data processing, predictive analysis, and automation that can offer the emotional understanding and critical thinking that humans provide. AI shouldn’t be seen as a standalone solution though, but as a tool that when effectively integrated, can drive innovation and transform operations.
You mentioned conversational AI. How does it integrate with other technologies to provide a holistic customer experience?
AN: Conversational AI acts like a central AI hub that brings together different technologies to deliver a smooth, personalised, and efficient customer journey. But conversational AI goes beyond basic conversation. One of the key technologies is natural language processing (NLP), that allows for conversations between customers and automated systems like chatbots feel more natural and familiar.
NLP helps chatbots talk like humans and minimize misunderstandings during their conversations, while automation technologies such as virtual assistants, live chats, and smart suggestion boxes enhance the way businesses engage with their customers during a conversation-based interaction process. In healthcare, patients can message the clinic asking to book, reschedule, or cancel appointments without waiting on hold for long periods. Using NLP can make the entire experience more personal and give them the impression they are speaking with a human.
Context helps businesses be more effective in delivering customer outcomes and customer data platform (CDP) can help with that. It transforms customer data from digital interactions and touchpoints into intelligence through data aggregation, activation, and analysis capabilities to create a single source of truth. For instance, not everyone has time to give feedback on their customer experience but answering a few short questions with an AI chatbot makes the process easier. This provides businesses with more data on how to improve and make the conversational experience feel more natural and intelligent.
Data from conversational AI can be better analysed with analytics tools, giving insights into customer behaviour, preferences, and pain points. These insights then guide product development, marketing strategies, and customer experience improvements.
In commerce, conversational AI is shaping the future of customer interactions. By combining various technologies and back-end systems, it makes it possible for personalisation of the customer journey. This means customers can get real-time updates on things like inventory, order status, and shipping information, ensuring they always have the most accurate details.
What are some ethical considerations when leveraging conversational AI? How can businesses ensure they are using AI responsibly?
AN: AI is stepping into roles we once thought only humans could handle, and it is becoming a bigger part of our everyday lives. However, AI is not without its challenges like privacy concerns, bias, and hallucinations. That’s why it is crucial to put fairness, transparency, security, and accountability at the core of ethical AI. These principles will guide us every step of the way.
To get started on an ethical AI journey, a thoughtful and smart approach is important. It begins with understanding the specific needs of the specific industry and aligning AI initiatives with both corporate values and societal expectations. This could be:
- Understanding the industry and purpose the solution is designed for as each industry can have a different effect on ethical considerations like technological access, geographical location, cultural nuances and more.
- AI tends to segment people based on learned biases from data. To correct this sort of group bias, you will have to train the model to ignore attributes like race, class, age, and gender.
- Set measurable goals. This helps to evaluate success in terms of the technical fairness of the AI solution and the social context it influences.
- Assemble a skilled team of experts who can steer your AI initiatives in the right direction. Start by including a customer experience team who can help figure what works for your customers. Then, bring in AI experts who can develop solutions that are accurate and ethically sound. Finally, collaborate with solution providers to scale your offerings and launch it.
By following these steps, businesses can now set themselves up for an AI strategy that is powerful yet responsible as AI regulations take shape.
