The next wave of smart apps is upon us

Erica may not go down in banking history as path breaking despite some astonishing capabilities. Unveiled in October 2016, Erica is Bank of America’s financial assistant—a chatbot that keeps track of your spending habits and credit scores, suggests neat ways to reduce debt and improve savings, and even directs you to watch educational videos. Soon, Erica will team up with Zelle—a peer-to-peer mobile money transfer service. Along with Zelle, Erica will be able to pay parking tickets, utility bills, send a cash gift to the significant other, pay tuition fees or buy a cup of coffee—using natural language interaction.

Like Erica, there are scores of intelligent and autonomous applications turning up everywhere; and that’s why, despite being among the ‘pioneers’, Erica may not stand out in the long run.

These developments indicate that the next wave of smart applications is already upon us. Smart applications are ‘contextually aware’, use natural language as the interface, plough through mountains of data to arrive at answers and solutions, work with a high degree of accuracy and can do all this in real time. These applications are built with a cloud-first, mobile-first and voice-first approach—which they combine with emerging technologies such as artificial intelligence (AI), analytics, deep learning, machine learning, natural language processing (NLP) and cognitive computing. Ultimately, using concepts such as containers and next generation integration technologies, they will be able to reshape and self-govern themselves.

With tremendous resources at their disposal, smart applications will be able to analyse networks and sniff suspicious activity, identify phony transactions, flag market manipulation, detect opportunities for improvements in customer interactions, recognize and predict snafus in production and sense impending disruptions in supply chains. In the next few years, smart applications will, quite literally, transform how we talk to banks, factories, warehouses, governments and businesses—and how these entities respond to us.

Every business can add ‘smart’ to its applications. Till now, creating smart applications that were intelligent, autonomous and aware was not easy. It required large budgets, access to vast amounts of data, sophisticated models and algorithms and a team of trained data scientists. But with the availability of cloud infrastructure, the growth in the internet of things (IoT), wider adoption of open source platforms and the pervasiveness of application programming interfaces (APIs)/micro-services—coupled with more affordable data extraction and analytical and predictive technologies—this is changing.

Infusing applications with intelligence and making them smart hinges around four imperatives—the building blocks of a smart application strategy:

Smart interactions

When gestures, touch, body movement, speech, and vision are used naturally to interact with applications, the intuitive experience makes manipulating and controlling processes simpler. Such unmediated interactions, often enhanced by AI and virtual reality (VR), need to be captured accurately so that they can be translated into action. For e.g., in the case of a conversation with a doctor, a smart application can capture details of the interaction to automatically schedule hospital appointments, and alert care givers, payers and patient monitoring systems to future needs.

Smart processes

Smart processes improve the accuracy and agility of business operations by taking advantage of adaptive business process management (BPM), cognitive process automation (CPA), robotic process automation (RPA), machine vision and autonomics to extract and process data and continuously improve via self-learning systems. They can be applied to make sales forecasts in retail, indicate the presence of minerals in mining operations and manage inventory in manufacturing, among other uses. For e.g., insurance customers can be on-boarded by uploading scanned digital documents and then using CPA and RPA to complete all back-end processes.

Smart platforms

Smart platforms help to rethink ‘systems’ as ‘platforms’—the underlying purpose being to provide differentiated business capability and a richer customer experience on these platforms. For example, a manufacturing execution system (MES) can take advantage of APIs and micro-services to enable increased reach, build new revenue streams and provide faster service management. Take the case of the customer of a print service provider who uses printers in multiple locations and who may have moved many of the machines from their original locations. A smart platform will not only let technicians log onto a web app and locate where a faulty printer is located (using sensors installed on the printers) but also allow them to acquire operational data, analyse the fault and automatically dispatch the nearest service technician to fix the printer.

Smart security

We have been witnessing a rise in the number of threats and vulnerabilities from unchartered corners in the last few years. The advent of IoT and smart applications or a connected ecosystem has pushed the boundaries within which security threats can be detected, responded to or prevented. Today, apps are no longer confined to one location or one data centre. They are everywhere—on mobiles, desktops, wearables, autonomous drones and self-driving cars. This calls for security to be built into apps at multiple levels. Smart security is a holistic security approach that only not protects the ‘applications’ in question but also guards the whole organization ‘perimeter’ including—but not limited to—users, data and infrastructure. Smart or new age security takes advantage of the power of cognitive computing and machine learning to pre-empt attacks that were unheard of and undetected in the past.

From a user experience point of view, smart security focuses on ensuring that end users are not inconvenienced by authentication and validation processes even while maintaining extreme security. For example, in the case of a bank account, user security can be based on a number of variables ranging from the transaction value, user behaviour, user location, network and the device being used. Depending on the indicators from each variable, the level of authentication required can be systematically raised—from a secure passcode to matching a fingerprint or voice sample and even prompting the user to capture and upload a selfie for authentication.

Combine smart interactions, processes, platforms and security, and we have applications with intelligence embedded in them. They interact seamlessly with users. They are intuitive and, therefore, help accomplish tasks more efficiently. They take advantage of data from internal and external sources, thereby improving decision making. They also improve customer satisfaction and drive growth. And let’s face it—they are cooler than anything we have used in the past.

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