Investor enthusiasm for artificial intelligence (AI) soared to unprecedented heights last week, fuelled by remarkable performance from chipmaker Nvidia, which propelled stockmarkets across three continents to historic highs. The surge, commencing on Thursday and extending through Friday, saw Nvidia surpass Google’s parent company, Alphabet, to claim the coveted position of the third most valuable company in the US, boasting a market capitalization of $2 trillion, second only to tech giants Microsoft and Apple.
Nvidia’s significance in the AI landscape cannot be overstated.
The company produces chips essential for training and operating AI systems, facilitating rapid data processing crucial for applications like chatbots. As demand for such infrastructure skyrockets with major tech players entering the AI arena, and with consumer interest in AI-driven products like ChatGPT and Midjourney surging, Nvidia’s robust performance underscores the thriving demand for AI technology, inevitably attracting the attention of investors.
The artificial intelligence (AI) boom has raised many questions, not least over safety and the impact on jobs, but there are also concerns that it might be driving unsustainable market exuberance.
What do consumers think of AI?
Consumers are still in a wait-and-watch mode with respect to AI, with feelings of both awe and distrust.
This is driven by the concern that it could replace a human they can connect with. The desire for human connection reflects in their channel preferences, too – with most still preferring to interact with human channels over digital, especially for high-stakes tasks like resolving an issue with a bill, and switching to digital for simpler, transactional activities like checking an order status. Human interaction remains a top choice when considering aspects of decision-making, customer support, and returns or cancellations.
There is also enthusiasm. Around 57% Indian consumers would prefer using Artificial Intelligence (AI) tools rather than to engage in human interaction while looking for products and services online, findings of a recent Adobe survey reveal. Recent research by Qualtrics tells us that 73% of consumers are fine interacting with AI is getting status updates on an order placed; and 48% of people are comfortable interacting with an organisation/ brand’s AI.
Where are businesses with AI adoption?
While shoppers try to work out exactly what to think of these technologies, the businesses that move quickly to incorporate AI and new data strategies into their operations will be best poised for success. In the early days of gen AI, it feels a lot like giving a toolbox to every employee and allowing them to experiment with what they could build, and possible gains in productivity and cost. As business use cases become clearer, we should be able to see how brands discover opportunities to drive innovation.
Offering a consistent and accurate customer support experience is one of the main challenges which businesses face. This is where businesses in India are still in the early stages of AI deployment.
Only 15% Indian brands are leveraging generative AI to enhance customer experience (CX) initiatives compared to 18% globally.
41% of Indian brands are seeing CX as a business priority today.
87% of Indian brands are prioritizing CX enhancements over other business goals.
76% of brands already have or will pilot GenAI solutions to support CX.
Overall, 53% of Indian brands want to improve GenAI capabilities in the next 12 months.
Bridging the gap between intent and action is going to be a priority in 2024.
As consumers go from making a purchase to resolving an issue online, the customer journey often breaks down – with satisfaction 22 % points lower compared to making a purchase.
AI and Customer support
For companies that get digital support right, there are significant rewards. One study found customers are 2.7X more likely to return after a positive digital support experience — the highest of any channel and journey studied.
Marketers must look to AI to empower their frontline teams with the tools, time, and insights to build stronger connections with customers and make that a better experience, too.
While AI will undoubtedly help businesses make simple, repeatable tasks more efficient – something consumers welcome - an effective AI strategy is not simply deploying more chatbots and automating tasks.
Blinkit, the quick commerce platform of Zomato has introduced a new feature called ‘Recipe Rover’ driven by the most popular AI models ChatGPT and Midjourney. Recipe Rover displays multiple recipes related to the food items which the customer searches for in the app. The company also plans to integrate generative AI into product photography, customer support, etc. Zomato’s massive customer database can be effectively deployed to create more customer-friendly features in the future.
Using data to predict customer needs
Data will dictate how to best use gen AI – for both customer and business needs. While businesses are still in the experimental phase, the push to monetize gen AI investments and quantify their value is becoming stronger. Leading that charge are decisions around how to use valuable internal data to maximize the value that generative AI is creating.
AI’s predictive power enables brands to get ahead of customer needs through analytics of behaviours, interactions and preferences. It identifies subtle shifts that human analysis alone could miss, such as churn risk, service issues, up-sell opportunities or optimal times for engagement.
These insights allow brands to engage contextually at just the right moments. Inevitably, while booking a flight ticket, the AI nudges me to book travel insurance as well. It makes excellent recommendations for hotels at the destination, often offering up significant discounts.
Identifying customer needs through prediction is just the first step, though.
Leading insurance tech company Policybazaar has been using AI tools for fraud detection using an AI-based risk framework that checks for liveliness and avoids deep fakes. It also uses AI tools for motor vehicles inspection where the customer can make a video of the vehicle and upload it while the AI does the damage assessment.
The company has also developed predictive AI for voice to text conversion which can be used to gather consumer data and be used to assess consumer behaviour.
Firing up Contextual Personalisation
Companies that grow faster drive 40% more of their revenue from personalisation, according to a report by McKinsey & Company. But tailoring engagement across channels and customers is enormously difficult. AI systems can take individual customer insights and orchestrate relevant cross-channel personalisation at scale. The result is a tailored, proactive experience for every customer.
When you think of your best customer experience, you realise that the brand seemed to truly understand and cater to you – personalised engagement is the magic behind this experience. It’s impactful, and it matters. It not only elevates the customer experience but also results in better business growth, because they return and keep ordering.
An e-commerce platform can use real-time behavioural analysis to recommend products to a user based on their current browsing pattern. When a user looks at sports shoes, the platform can immediately recommend relevant products, such as sports socks or training equipment. This immediate, relevant personalisation improves the user experience, leading to greater engagement and potential conversion.
With 62% of consumers comfortable booking an airline ticket through AI,
MakeMyTrip, one of India’s leading travel booking companies has collaborated with Microsoft to use generative AI to introduce voice-assisted booking in Indian languages. It helps users by offering personalized travel recommendations based on their preferences, curating holiday packages and booking them.
Being mindful of privacy
While AI offers immense potential, it also brings significant risks if ethics and consumer privacy are neglected. Around 59% Indians do not feel positive about buying from a brand that isn’t transparent about the use of their personal data.
To maintain ethical integrity, brands must establish clear guidelines for unbiased, transparent and privacy-focused use of customer data. Rigorous testing is essential to eliminate bias in predictive algorithms.
There are three essential steps that companies can take to find the sweet spot between personalisation and data privacy.
- Only collect data that’s essential to creating a better customer experience. Begin with the experience you want to deliver and then define the data required to deliver it.
- Allow your customers to customize their experience. Let them choose how much personalisation they want and how much of their data they are happy sharing.
- Be transparent about how their data will be used. Once they understand that, they will be more likely to share their data willingly.
In a nutshell, think of AI as the neighbourhood chacha (uncle) at the kirana (mom- and-pop) store. They have all your weekly transaction data. They know everything about you and your family. And they use that information to give you personalised, unmatched customer service, while maximizing their profit.
Pretty basic, right?
Kunal Sinha is a senior strategy and foresights executive based in Jakarta, Indonesia. He is the author of several books including The Future of India’s Rural Markets and Raw – Pervasive Creativity in Asia. He writes for MxMIndia every other Monday. His views here are personal.