Talking AI: impact and promise

After decades of talk, research, and experimentation, artificial intelligence (AI) is finally taking off in the mainstream commercial market, as companies deploy AI to disrupt their business models and transform operations. Examples are everywhere—from biometric facial recognition on our smartphones and predictive maintenance for equipment and facilities to personalized customer experiences. And yet, despite all the advances, we’ve only scratched the surface of AI’s potential impact.

Trust: the linchpin for pervasive AI adoption

How far and fast will AI adoption move? It’s no longer a question of technology as an obstacle. AI tools have matured to the point at which their ability to operate effectively is now a foregone conclusion. Instead, AI’s growing adoption and impact on businesses hinges on trust.

Think about manufacturing and distribution. AI-powered machines are becoming commonplace in every part of the production process and are playing key roles in handling goods in distribution centers. But it’s a big leap of faith to go from trusting robots to weld a seam on a car door or pull apart from a warehouse shelf to putting our lives in the hands of AI that maneuvers driverless cars.

It’s the same in healthcare. Today, AI-driven robots perform various surgeries, with oversight from doctors, with amazing accuracy and stamina—and few people give it a second thought. But what happens when AI is the driving force behind such things as genome sequencing, connected wellness, and personalized treatment regimens and medicines? Will people trust a machine to make what could be a life-or-death medical decision?

No matter the size of a company, trust is key to more pervasive use of AI. There are still entrenched biases among people whose career is based on how they use data to make decisions. Think about marketers trying to understand consumer sentiments, product developers figuring out which new features customers want, or human resource professionals determining which candidates will best fit their organizations. How fast these professionals can let go of tribal knowledge and trust the machines and algorithms will dictate the speed at which AI grows in the future.

As trust is earned, we’ll see increasingly bolder, and transformative uses of AI. Adoption will likely be more intuitive and smoother—for two big reasons.

COVID-19: changing attitudes and behaviors

The first reason is COVID-19. The pandemic forced billions of people, even those who weren’t necessarily technology savvy, into a digital-first existence. And, by and large, it worked well. People saw firsthand how digital technology, including AI, enabled them to work remotely, shop for many more things they hadn’t before without going to a physical store, and find new ways to entertain and educate themselves in the comfort of their homes. And the speed with which this adoption happened was breathtaking, illustrating people’s capacity for rapid, significant change in attitudes and behaviors.

At the same time, digital has underpinned countries’ efforts to understand and respond to the virus. Analytics and AI helped—and are still helping—medical researchers and health departments crunch massive volumes of data to understand, in real-time, how the virus was mutating and predict the impacts. Analytics and AI capabilities also were key to rapidly developing and rolling out vaccines and tracking the drugs’ ongoing adoption and efficacy—again, in real-time. This experience is a great foundation for companies looking to accelerate and expand their use of AI to build.

Cloud: helping lead the charge

The second driver fueling quicker and easier adoption of transformative AI is cloud, which is the unifying digital fabric that enables companies to achieve sustainable, purpose-driven value. Cloud has democratized access to and deployment of powerful, leading-edge AI and machine learning (ML) tools that, in the past, companies developed on their own. Google Cloud, for example, offers ready-to-use and ready-to-deploy AI and ML capabilities that companies can quickly, intuitively, and inexpensively tap into to transform their business. TCS and Google Cloud help companies extend the value of cloud so they can innovate and realize the cloud’s true business potential.

Consider the experience of a major U.S. bank that took advantage of Google Cloud to transform its data and analytics platform. Rather than undergo a time-consuming and costly expansion of its own on-premises data infrastructure, the bank is using Google Cloud’s BigQuery platform to run analytics and AI and ML models on its data for future business predictions.

Another example is an Australian grocery chain that used Google Cloud to shift from a gut-feel-driven merchandising approach to a proactive, data-driven decision-making process. Google Cloud’s AI tools now enable the retailer to create product assortments specific to individual stores, dynamically optimize what’s on each store’s shelves, and create faster business cases with more “what-if” simulations. The result: a $150 million boost in sales over five years.

A third company, a United Kingdom-based retailer, used Google Cloud’s Contact Center AI and its speech recognition capabilities to automate calls to stores, increase personalization, and better serve customers through digitally-enabled contact centers. One example: The platform enables call center staff to program seasonal event-related vocabulary (e.g., “snow shovels”) directly into the system to handle specialized customer inquiries more quickly and effectively.

These are just a few examples of AI’s transformative power. And they provide a glimpse of what the future holds—to the benefit of companies and their customers everywhere.

This is the first in a series of articles authored by Nidhi Srivastava , Vice President and Global Head, Google Cloud Business, TCS

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