Success in the enterprise segment is highly dependent on making better and more informed decisions
By Kumar Srivastava
Indian businesses have been severely impacted due to the perils of COVID-19 and the several partial and complete lockdowns. Though our economy is in a state of recovery and markets are slowly opening, the new normal has impacted the buying capacities of customers. Understanding the sudden change in buyer behaviour, businesses are now more than ever required to deploy strategies that resonate with the buyers and market their products in a manner that nudges customers to make the purchase. This is where integration of AI in enterprise can play a significant role in shaping and helping Indian businesses come out of this slump.
Enterprises essentially depend on two key ingredients for sustained success; timely, swift and loss-less transmission of information and the speed, veracity and efficacy with which decisions are undertaken. Both these ingredients are pivotal and essential for profitability, increased customer satisfaction and continued employee happiness. Not just limited to business and sale related strategies, enterprises can also leverage AI to maximise value in internal operations, like HR, Finance, and also to increase efficiency, value and quality in systems, workflows and processes.
Success in the enterprise segment is highly dependent on making better and more informed decisions. Fortunately- unfortunately, most decision-making in an enterprise comes with its own set of challenges. During such instances, a business has the option to turn to AI to help in leveraging data-backed information that will help in directly targeting the defined customers and moves away from the age-old method of hit-and-try of strategies. Since enterprises are tapping a signal that is otherwise not available to someone else, it gives them an edge.
Enterprise AI is all about using data-backed analysis and signals that will help in mapping the results prior to inclusion of the strategy in the businesses. There is always a lot of information all around, the question is- who can best collect, aggregate and analyze that information as fast as possible, to come up with that competitive advantage.
Secondly, most data collected manually from multiple and disjointed systems in an enterprise is hard to combine and merge to address different problems. Enterprises need to ensure that their data is organized, accessible and interpretable.
Key enterprise data includes customer data, customer interaction data, business transaction data (such as orders, production and shipments), and business operations data (such as operational logs, network activity, IT tickets, HR tickets, financial data and application data) that includes the access, activity and management of applications that directly or indirectly deliver value from the enterprises to its customers. One common mistake a lot of companies make is trying to solve different problems with one solution. To create a 360-degree view of the business, customers and the ability of the enterprise to serve its business needs, these disparate data sets need to be merged together to reveal the forest among the trees. This is a complex undertaking and requires a level of data maturity that needs to be developed as part of any digital transformation efforts. Automation is also critical for enterprises to digitally transform. The ability to automatically collect signals, determine intent, sentiment, persona and need, and automatically move the levers of enterprise services and systems to deliver on the request, need or action is fundamentally required for an enterprise to be more agile and innovative.
Though at a nascent stage in the world of technology, multiple large-scale industries across the world have adopted Enterprise AI to help understand their customers better and spearhead strategies that they resonate with. For example, Mitra QSR, one of the USA’s top-50 franchised restaurant operators with more than 200 KFC and Taco Bell locations, recently leveraged the expertise of Hypersonix to deploy enterprise AI solutions to optimise their functioning. Owing to the solutions introduced, Mitra QSR was able to sustain during the early lockdown days by better understanding customer behaviour, streamline menu options, and get store-by-store business insights and strategies within minutes, making it easier for them to implement them on time.
A 2020 report by NASSCOM estimates AI and data science to potentially add $450-$500 billion to the Indian Economy. Indian enterprises must speed up their digital transformation to fully leverage AI and extract value from applying AI into their decision-making processes- both for internal as well as external operations. They need to drive their agility by enabling unfettered access to data, compute and enabling a high degree of integration and automation. One way to achieve this is by tapping into one of the hottest sectors within the software industry, enterprise AI platforms.
With infinite data to be mined from India, machine learning stimulates the algorithm the way the human mind works, providing near to accurate solutions to the issues. The introduction of AI in India’s enterprise segment along with technical talent will not just help in reducing the time taken to identify a fitting business and communication plan of action but will also put forward ideas related to pricing, and promotions faster and more accurately, making the demand for enterprise AI even more noteworthy in shaping the Indian business in the post-pandemic world.
(The author is chief technology officer, Hypersonix. Views Expressed are personal.)