AI trends in the US that Indian companies can leverage

Artificial intelligence (AI) is everywhere. AI is at the core of disruption across industries globally. In the US, AI has successfully enabled convenience and faster decision-making on a significantly larger scale than ever conceived. For example, AI is a key tool for Netflix, which uses data about subscribers to recommend movies.

AI is rapidly applied among businesses in India too, but with some limitations. Internet connectivity in rural India, data maturity among organizations are some deterrents to achieving the scale at which US businesses apply it. While Indian businesses circumvent those limitations, here are some AI trends that Indian companies could apply.

Image recognition and object detection

Image and object recognition have been largely used for classifying objects. Indian companies, especially retail, can use it not only to identify objects in an image but also location and other information such as text and colours. It can also be used to build context around the objects detected – for instance, whether the scene is indoors or outdoors, or the presence of other objects. This enables users to define the objects precisely and gather data that can be used for further analysis related to marketing, design or consumer behaviour. For example:

• Consumer electronics: To identify and analyse smartphones, gaming consoles and other gadgets

• Search engines: To retrieve data from search engines using images

• Security: For facial recognition and tracking

• Transportation: To detect and track autonomous cars to gather information for road safety

Voice-based AI and speech recognition

Research and Markets reported that speech/voice-based AI market will be worth $18 billion by 2023. As voice recognition technology gets bigger and better, it could be incorporated into everything – from phones to refrigerators, cars and other home electronics. Two primary consumers for voice-based AI have been smart home/smart speakers and mobile platforms. Indian technology and IoT companies can look forward to adapting it to develop speech and voice-based AI solutions of their own.

AI-generated marketing content

With AI algorithms, we can do more than just automate systems and processes. Machines have been independently generating content for years. Marketers can utilise this ability to automatically generate content for simple stories such as stock updates and sports reports. Companies such as the Associated Press, Yahoo! and Fox have been using them for quite some time to curate content. Other applications where AI is used for generating content include:

• Chatbots

• Custom news feed algorithms

• Abstractive summarization, which involves selecting the most meaningful sentences in an article and arranging them in a comprehensive manner.

Hyper personalisation

We’ve come a long way from traditional marketing methods, which included mass messaging and generic content formats. With technological and digital development, communication has become highly personalised. This hyper personalisation is a more advanced next step towards personalised marketing, leveraging AI and real-time data to share relevant content, product and service information with customers.

Hyper personalisation technology can perform data collection, customer segmentation, targeting, measurement and analysis.With a diverse population to engage with, Indian marketers can look at AI algorithms to identify audiences and share curated content as per their tastes and needs.In India, the finance and retail sectors have been using AI to support business decisions as well as for customer support and engagement. However, there is scope for applying AI to various internal business processes to achieve greater results.

While Indian companies possess the requisite AI know-how, the true success lies in mindful application. Here are some simple but important rail-guards that could help as companies apply AI to business.

• Start with a business problem: What are you trying to solve by using AI? Is it managing inventory or do you want to win more customers or improve their loyalty? Defining a clear objective for the project will guide the application.

• Have the right skills and data: Gather the relevant data and involve data science experts to understand it, identify the tools needed to analyse it. This is critical if the problem identified is to be solved.

• Measure impact against KPIs: Monitor your AI solution and continuously measure performance to ensure it’s on track and in line with the project’s objectives.

Sunil Mirani, Co-founder and Chief Executive Officer, Ugam, A Merkle Company