The biggest opportunity in the futures lies in the application of AI, not in its implementation, and even more "NOW" in these difficult times, this article will help you conquer all your fears and make you believe even you can "Apply AI now"
As a business professional, you know can grow with AI, but a lot of us get stuck believing AI
be very complex, assuming it will take time, I will have to hire a data scientist, and are unsure of the results it will deliver. Here are some answers to your questions, which will get you started
Is AI Complex?
With the exponential growth in AI technology, giants such as Amazon, Google, and Microsoft have come up with platforms that allow for the development of AI technology without the need for coding. This has shifted the focus from learning the coding language and instead given space for more ideation and creativity in solving business problems.
AI takes time to implement?
With the advent of Indian start-ups such as Uniphore, Rezo.ai, Wobot.ai we are also seeing a change in the global application of AI technology shifting from buying licenses to subscription-based models where you pay as you use. This has also shifted the implementation time from months or years of development, and then usage, to almost immediate usage with the software being provided as a service.
With IRCTC and CultFit as clients, Wobot uses AI to detect food hygiene and other safety parameters. Its plug-and-play tool is connected to an existing CCTV or any other camera to help detect and track anomalies in standard operating procedures (SOPs) currently looking into hygiene, food safety, pilferage, and customer experience.
AI requires hiring a data scientist?
While there are situations that require hiring a data scientist, it is not a necessity for implementing AI in your business. There exist multiple APIs and code-free platforms that can be utilized instead to ease business functionality and increase efficiency as well as various start-ups providing machine learning as a service that can be adopted by businesses.
AI results are not quantifiable?
There are various methods to ensure results that can be looked into such as doing simulations, having a control group, and doing a limited pilot. Quantifying ROI is heavily dependent on the context and data of the organization used to train, test, and refine the AI model in case of a custom application of AI.
Tanveer Khan of NTT Data states that “Uniphore’s solution is helping reduce costs and customer service advisors’ time by automating mandatory after-call tasks.” This improves the availability of customer service advisors, making customer service their sole focus and improving the quality of the service being provided by the business. “With Rezo.AI’s email automation solution, brands will be able to understand their customers at a deeper level, and predict what they really want, helping them craft relevant campaigns and product experiences at an effective cost", Rashi Gupta, co-founder and chief data scientist, Rezo.AI, said.