Using AI to Solve Business Critical Problems
Artificial Intelligence (AI) is the concept and study of systems with the sole aim of replicating a human’s thinking structure amalgamated with the processing power of a supercomputer. The end-goal of such systems is to make relevant decisions while taking into account both material and human factors involved in a situation. Due to this unique nature, AI systems in action are expected to be better equipped to handle pressing situations and crisis as compared to their human counterparts who always have a margin of human error while making a decision.
Rightly so, AI is a transformative technology which is widely accepted to be the backbone of all business in the near future. Think-tanks and discussion groups in every industry, be it healthcare, automation, automobiles, medicine, and research, are abuzz with what AI can do. However, all of these applications stretch at least 10-20 years in the future.
The question we should be asking is: what can AI do for us, right now? There are a lot of existing problems that AI can solve for us and help provide economic and sustainable solutions that work way better than the existing infrastructure.
AI for Communication Service Providers (CSPs)
CSPs are functioning in an increasingly competitive market, still hesitant about whether or not to integrate AI in their systems, the extent to which they should adopt AI, and which business verticals are ready or not yet ready for AI solutions.
CSP has a three-pronged opportunity with AI: intelligent marketing, intelligent customer care, and intelligent insights.
The existing AI technology is adequate to provide CSPs with:
- personalized customer sales (preparing and tearing down personalized usage packs and offers) and a faster response to such inquiries and demands.
- Determining which new products should be added and which ones should be scrapped from a CSP’s products’ catalog (by studying competitor data, customer trends, sales data etc.).
- Enabling cloud-based support systems, software-defined networks, self-optimizing networks, and network function virtualization by building on telecom network analysis and optimization.
- Setting up cybersecurity and fraud detection mechanisms.
The list here is by no means comprehensive, depending on the unique demands of a CSP, they can customize what AI does for them. The key point here is, through this partial AI upgrade, CSPs can not only drive good ROI, improve performance, and boost profits, but also prepare their workforce to welcome AI in its full glory and develop in-house capabilities to tackle the upcoming AI revolution.
Using AI to identify Business Opportunities
Expanding your business horizons is among the most important tasks an organization takes up. The right decision at the right time can prove revitalizing, while a wrong decision may prove lethal.
The existing AI technology is capable of helping you make this decision with its highly efficient analytics applications. These systems can process and draw results from a bewildering array of data points and factors across industries, that a huge team of human experts might not even see.
Further, AI analytics can help your organization in drawing intelligent insights from customer data at your disposal to unravel the space for a new product. Such highly customized products prove pivotal in helping an organization gain an edge over competitors.
Using AI for Digital Transformation
Organizations are increasingly sensing the need to provide self-service interfaces to users which their users can then leverage to personalize their experience. In markets that are highly customer-centric, such facilities will soon become the focal point.
Existing AI solutions like digital assistants (think Alexa, Bixby, Siri), chatbots, software-based networks, cloud-based management systems, and data security and fraud prevention capabilities in these solutions, are central in driving an organization towards incremental AI adaptation.
The use cases mentioned provide just a glimpse of what AI is capable of doing for you already.
Integrating AI in your business is not a technological leap but also a journey. The first challenge most organizations face is recognizing area which can benefit from the existing AI solutions. The next issue is finding the right help and talent who can make this transformation fruitful. A recent poll by E&Y revealed that lack of talent is the biggest hurdle an AI implementation project faces. Finding the right support is hence critical to an organization’s AI journey.
Needless to say, the right data is crucial for the functioning of these systems. It is entirely correct to say that an AI system is as good as the data it has been trained on. Hence, it becomes even more important to find the right people who will enrich and process your data properly before feeding it to the prospective AI system.
(The author is a Solution Consultant at Sahaj Software and the views expressed here are his own)