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Digital Transformation – The Great Game – Part 3 of 3 – What do Blockchain, AI, IOT and APIfication Mean for My Business?

In Part 3, of our 3-part series of “Digital Transformation, The Great Game“, we will talk about some of today’s mega technology trends around Blockchain, AI, IOT and “APIfication“. There is enough information about all of these in plenty of other news sources, so I have no intention of defining each; my purpose for writing this series is just to give a Layman’s view of what can a business do with all this advanced technology in simple terms.

Now, I am sure that some of the readers may have different opinions about my views, but that’s the beauty of blogging online i.e. we can all get along just fine by appreciating everyone else’s views as well.


I have been asked by several folks about what I think regarding Blockchain. Since Blockchain is the underlying technology behind Bitcoin (which as of today was trading at $15,000), my answer is pretty simple and no different than many others.  Blockchain “could” be the biggest thing that happened to us on the Internet.

The Cryptocurrency Use Case for Blockchain is pretty clear, but where I struggle with Blockchain is what can a Business do with Blockchain Technology today?

Blockchain Technology being a “Shared Ledger” inherently relies on a “Consensus” mechanism between multiple trading/transaction parties. In a Cryptocurrency use case, the Consensus is achieved by multiple independent computers solving mathematical/crypto problems through a process of mining. But let’s look at the idea of a “Shared Ledger/Database” between various organizations (many of them compete with each other).

Within the internal bounds of an organization, it is relatively easier to achieve “Consensus” protocol, however, achieving a consensus between multiple organizations requires consortiums, conflict resolution and information security protocols and agreements which have to be hashed out before the technology can be used to its full potential; add regulatory issues and the problem becomes even more complicated. Maybe Blockchain will evolve just like Cloud, where you have private, public and/or hybrid Blockchains (Ledgers), but the reality is that in most cases Blockchain Technology is not out of the R&D stage and has not gone mainstream just yet. But the power of a “Trusted Shared Ledger” is not to be ignored and it will eventually disrupt many existing “intermediary” based business models. Our advice is to keep learning, experimenting and watching so you are ready to jump in at the right time.

Artificial Intelligence

This brings me to the next hot topic i.e. AI. Yes, AI is here in its many forms (Natural Language Processing/NLP, Natural Language Generation/NLG, Machine Learning/ML, Deep Learning/DL, Neural Networks NN, Robotic Process Automation/RPA, Smart Process Automation/SPA etc) and is here to stay and grow exponentially. The underlying Statistical Models and Mathematics behind AI have been around for a long time, however, the advancement of Cloud Computing power and innovations by the likes of Facebook, Google, Microsoft, IBM etc have evolved AI to a point where all of us can consume AI as a utility in many cases. Many of us use the words “Artificial Intelligence” to intimidate each other but most of have been Consumers of AI for a long time (Alexa, Siri etc). Developers who consume AI models using Google TensorFlow, Microsoft Cognitive, and other tools are usually not intimately familiar with the inner details of the AI Models (and they don’t have to be).

A typical set of problems where AI can be applied include process automation (using RPA and SPA) within HR, Finance, Procurement, etc. as well as predictive data analytics for different types of Business Forecasting, Sentiment Analysis around Customer Service, Chatbots for managing Customer Acquisition/Retention and many more.

Today, if I have an AI problem to solve, I need to define my problem, look around existing AI frameworks to see what AI model fits my need, train the model, if need be, and start using it. Many of the AI models inherently improve the outcomes as we train them. The selection and training of AI models are where things start to get a bit more complicated and this is where the role of Data Scientists come in. The Data Scientists are sort of “programmers on steroids” with a deep understanding of the underlying AI models and training methodologies. There are many third-party websites (Algorithmica, Amazon AI, Kaggle, etc.) where you could buy existing AI models and even hire the Data Scientists on a temporary basis to have them develop and possibly train your models. However, depending on the type of your business, and your use cases, you may eventually need to develop your own internal Data Science team that works along with your IT and Business Teams. In summary, AI is ready for the prime time and even though the existing skill-sets within the enterprises are relevant, AI requires investing in additional skill-sets around Data Scientists and the retraining of existing Developers to be able to consume the AI models properly.

IOT & APIfication Technologies

IOT is already everywhere with almost infinite scope to grow. Although IOT impact is more prominent in industries such as Agriculture, Energy, Transportation, Manufacturing, Retail, Healthcare, and so on, one of the core “enablers” of IOT is the concept of “APIfication” which has broader appeal for the BFSI Industry as well. In fact, “APIfication” is one of the most important requirements for the so-called “Digital Transformation”. By “API-enabling” many legacy applications, the business can not only harness the power of integrating with internal and external partners seamlessly but also possibly identify new ways of monetizing their existing technology investments. As the API ecosystem grows, the API management systems have also grown along with it. API management platforms include: APIgee, Akana, Kona and many others.

If you don’t know about APIfication, I suggest you familiarize yourselves with the concept and spend some time studying it.

I hope this series of 3 articles was of some value to our readers, offering them some practical insights into these rapidly evolving technologies. Just like you, I am very excited about the business applications of these technologies and continue to be a student of, not just the Technology, but how we use them in the real world!