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How APAC is thinking about generative AI and the role of data streaming

Deepak Ajmani Profile picture for user Deepak Ajmani November 15, 2023
Everyone's talking about generative AI. But it's not all plain sailing. Deepak Ajmani shares the top concerns from businesses in the APAC region for Confluent.

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(Image by 756crystal from Pixabay)

Barely a day goes by without some new piece of research making a splash on the business pages providing yet another insight into the fast-moving — and fast-developing — world of generative AI (gen AI).

The speed at which generative AI is making it to the top of the boardroom agenda is breathtaking. Here at Confluent in Asia-Pacific (APAC), we saw an eightfold increase in enquiries in the first half of the year alone.

What links all the discussions so far is that businesses and organizations are looking to use gen AI to interrogate their own data to deliver near-human responses.

The business case for gen AI

For instance, an airline could use generative AI to deliver real-time flight information that provides a better user experience than simply waiting for an online arrivals or departures board to update. And if flight information were linked to an e-commerce platform, it could automatically deliver dynamic pricing to ensure no plane takes off without a full passenger quota.

Similarly, a bank may be able to use generative AI to provide details of someone’s current account or how much they owe on their credit card. On the face of it, this may appear to be a less than taxing task, especially since the information is available already. To do so today without generative AI would mean someone having to log on to a website or app — or calling a contact centre. And even then, the querying process may be clunky and time-consuming.

But with a generative AI-based system, the enquiry can be handled in a fraction of the time thanks to real-time data streaming — with information brought together from different data silos — working in tandem with a machine learning (ML) model and presented with the help of natural language processing (NLP).

As a result, enquiries are handled ‘in the moment’ based on the most current and up-to-date information.

This is more than a simple chatbot answering pre-configured questions. Put all those elements together into a solution and it becomes a dynamic customer-facing solution that can be plugged into any organization. On that basis alone it’s clear why gen AI is such a hot topic.

Gen AI will disrupt customer service, research, and advertising

With faster, more relevant, more personalized, and more up-to-date responses, generative AI has the ability to transform customer service - and potentially deliver increased revenues and improved brand loyalty., for example, uses real-time data to provide live conversation intelligence for its contact center customers, complete with reporting and analytics. When end users ask a question, the Large Language Model (LLM) platform automatically searches knowledge bases to find an answer. This frees up contact centre staff so they can focus on calls instead.

Plus, the technology provides a real-time transcript of each customer interaction — again, allowing agents to focus on the customer before moving onto the next call.

Of course, none of this could be done without using real-time data streaming services. Nor would it work if it could not be done at scale, since’s platform is capable of handling thousands of calls simultaneously.

But it’s not the only area being examined. Research companies are using gen AI to make sense of data — both current and historic — to create swifter, more meaningful insights.

One start-up in the environmental sector is using data streaming and gen AI to provide locally accurate weather forecasts that provide early warnings of storms, or high pollution levels in cities.

Advertising agencies are using generative AI to train models that better understand the interaction between consumers and brands to create personalized content.

Of course, digital advertising has spent years serving ads based on search history, demographics, and anything else that can help advertisers connect with their audience. The difference with gen AI and data streaming is that this can now be done in real-time making ads more personalized, relevant and timely.

Just like everything else related to AI, it’s a game changer. And we’re only just scratching the surface.

But it’s not all plain sailing. The race to adopt generative AI is being held up by a lack of data scientists and key personel with the right skills to staff this latest computing revolution. Of course, the IT industry seems to be permanently facing a skills gap. But in the case of AI, it’s particularly acute.

But the other big issue is understanding the wider impact AI might have on a business. Earlier this year Goldman Sachs published research, which predicted that AI could replace some 300 million jobs. It’s an issue with such far-reaching consequences it simply cannot be ignored.

Top concern for those embarking on their gen AI journey

And that's not the only consideration. Even before thinking about investing in AI, businesses first need to understand what they want to achieve. What does an improved customer experience look like? Is it the same level of service, just faster? Or is there some unique differentiation? And if so, what role does the data — and data streaming — play?

Even once this issue has been addressed, there is a question of cost. With so much data needed — often residing in different locations — businesses need to be honest with themselves about the task of linking all their data hubs so that information can be accessed at any time on demand.

Finally, there is the all-important issue of security. Without enterprise-level protection — both in terms of where data is stored and who has access to it — critical infrastructure and information will be insecure. If the data is not secure — if it's publicly available and accessible — it will be open to cyber attacks. The consequences are unimaginable.

Make no mistake. We are on the cusp of seismic change within the world of business with generative AI at the epicentre.

The opportunities are there, but generative AI must be adopted with careful planning, taking into account the implications for business transformation — and a real-time technology platform that is protected against rogue interests.

Based on the conversation currently taking place in APAC, this is exactly what's happening.

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