Artificial Intelligence (AI) is essential to every enterprise that is looking to be 'needed' than simply 'exist'. AI has started making inroads in every meeting of a large or small enterprise. Its presence is undisputable as the early signs of AI making transformational changes is promising. The subject has fascinated eyeballs with literally everyone making it sound like unescapable and vital. The question that remains unanswered is where we start from. Let us understand here.
AI is dignified to become single largest revolution because of the versatility it brings to thinking and decision making in every sector. As per a report by Accenture, business revenues can be up by 38 percent by investing in AI and human-machine collaboration. Gartner guesses that clients will be able to manage 85 percent of the connections with an enterprise without human interference in near future. Evidently, Big Data powered by AI and Machine Learning (ML) is transforming the way businesses are defined, designed and delivered and enterprise value is captured.
The key to start building AI and ML capabilities is technology and talent. The convergence of Big Data and Cloud powered by AI and ML is real now because of access to extraordinary storage and computing resources, better bandwidth and access to troves of structured and unstructured data. These three factors are instrumental in making AI a real revolutionary technology. At the same time, Human Resource departments need to rejig traditional ways of employee valuations and devote in building a multi-disciplinary workforce that can work in partnership with AI to reap out the profits AI is capable to human race.
Enterprises looking to build their own AI and ML capabilities need to have access to computing resources, humongous data sets highly available bandwidth and talent. Data is the next natural resource, similar to air, oil and water. Data will affect almost all facets of our existence, eventually impelling the way enterprises chase growth in a constructive manner.
The four Vs of data has been on rise and it has been challenging for enterprises to analyses structured data stored in silos with amorphous data generated by pools of social footprints, sensors and derive significant change out of it.
Businesses have to look for new ways to capture and store the data so that their data can be monetized effectively. Businesses will be able to build their AI/ML abilities around this trove of unexploited data to extract incremental value.