Organizations that are planning to jump onto the AI (Artificial Intelligence) bandwagon must make sure they have a sense of the business questions they are trying to answer with AI. What are the ways to generate new revenues, how to identify new customer segments and new product lines, or how to predict buying behavior – these are some of the important questions that must be asked before moving to full-blown AI implementations. This blog sheds some light on the key factors that are leading to AI going mainstream, the business possibilities and challenges involved, and how Ness can help organizations overcome these challenges to succeed with their AI initiatives.
The availability of data libraries is an important factor that is driving AI’s popularity and usage. Previously there were not many AI libraries available for use. Today, companies like Google publish libraries written in Python or R, which can do regression analysis in just one line of code. In less than 20-40 lines of code, you can complete the regression test analysis. This is possible because these libraries are Open Source technology, available for everybody to use. Libraries that once were available only to researchers are now accessible to all, thanks to social collaboration. Today a high school student who understands Python programming can learn Tensor Flow and build a neural network in less than three days. So, the major changes that have supported AI adoption are:
With these changes, it is now possible for people to build their own algorithms, without having to go to a research Ph.D. lab.
AI to Drive the Next Level of Business Opportunities
Image classification, natural language processing (NLP), and automated data cleansing are some of the use cases we are currently seeing. It is hard to fully envision the magnitude of impact that AI will have in the coming years, because this is just the tip of the iceberg, and there is certainly a lot more to come. But industries have started realizing the potential of AI in making revolutionary business transformations. Imagine all the connected devices like your watch, car, home appliances, personal health devices etc. throwing data into the Cloud somewhere. The combination of all that data gives organizations the opportunity to draw powerful insights to improve their processes, rethink business models and create personalized customer experiences. Wealth Management, Retail, and Manufacturing are just some of the industries that are poised for rapid AI adoption.
For example, in the Wealth Management space, AI robots are playing the role of wealth advisors who can create endless portfolio combinations based on client data (net worth, income, liabilities, buying patterns, etc.) and come up with highly customized and personalized platforms for them. Banks are also looking to invest in data science to find out what AI can achieve, within the regulatory framework.
Ness’s Strength in AI
Our Connected approach is a unique framework we use to engage with clients. When a Ness team goes into the Discovery phase, it can include a solutions architect who knows AI and machine learning, a delivery manager who is working with the client, a subject matter expert like a data architect, and a UX designer. This composite team of multiple skills engages with the client over a one or three-day workshop, to understand the real business challenges the client is trying to solve with big data or AI.
With a strong understanding of the business problem, we try to help the client through the Envision phase, where we discuss the best practices, do a proof of concept and try some prototypes to help the client envision a roadmap. We then create an implementation plan showing how Ness can help them implement this. The Ness Connected model is a powerful method of engagement – it reduces the risks and builds legitimacy.
Our product engineering focus is one of our unique advantages – we always talk in terms of features, road-map, agile development, faster time to market, automation and more. We have a critical mass of subject matter experts in the company who can coach in the areas of AI, machine learning and big data. With a global footprint, Ness is an ideal partner as you take your first steps into high-end technologies like Big Data and Machine Learning.