Is Your Enterprise Ready For The Growing AI Opportunity?

'Digital' has been pushing enterprises across industries to relook and reinvent themselves. Let's take the example of the launch of Jio, a mobile network operator in India. It has technologically leapfrogged traditional investments in 2G and 3G networks, to create an operating model that offers dramatically different products to customers at a fraction of the cost that it would take traditional telecom companies. So how can enterprises compete in this disruptive marketplace?

Artificial intelligence (AI) has come to establish itself as one of the enablers in a number of industries such as banking, retail, healthcare, manufacturing and telecom. It has become a competitive differentiator, and enterprises are now asking if AI can help them go a step further from being 'the solution', to helping them 'identify complex problems worth solving'. Recently, Demis Hassabis, CEO of Google Deepmind, pointed out that "If we can solve intelligence in a general enough way, then we can apply it to all sorts of things to make the world a better place,"

Consumers are embracing digital and rapidly adopting the large number of products and services being made available. Do enterprises have a choice then but to reinvent themselves to remain relevant in this environment?

The opportunity lies in finding the right problem to solve

The AI opportunity can be found in where data analytics, machine learning and robotics are heading.

According to industry reports, 45% of trading is done electronically. During its peak days in early 2000s, Goldman Sachs had approximately 600 traders in New York buying and selling stock on behalf of the investment bank’s large clients. Since then, auto-trading programs have taken over, learning and predicting better with every passing transaction. There are now just two equity traders doing the job. With this, financial institutions are keeping costs down while offering their services to larger numbers of people looking to plan their financial future. The benefits of this are obvious.

The demand for energy can’t seem to keep pace with supply. Machine learning techniques can be deployed to model the behavior of energy consuming devices and battery storage units. This enables energy grid operators to better anticipate demand and plan their access of renewable energy.

Expanding internet connectivity and Internet of Things makes it easier to access data from anywhere, both from the physical and digital worlds. A number of AI techniques have already exited the ‘testbed’ and made their way into the enterprise world, especially in the healthcare industry. For example, KenSci a Washington-based start-up has created a risk prediction platform powered by machine learning that enables healthcare professionals to uncover various kinds of clinical, financial and operational risks before a patient actually falls ill. This could reduce the cost of healthcare.

With AI on a growth trajectory, here are a few examples of what it will do in the near future, across industries,

  • Reduce fraud, financial loss and legal damages especially in industries like banking and insurance
  • Accurately read languages written in different form such as Google’s Neural Machine Translation system
  • Voice recognition that connects to enterprise data and provides customized service through smart digital assistants irrespective of employee or customer
  • Amplify potential of SMEs, by capturing their knowledge in AI based models, and AI tools are able to take intelligent decision/action. A ‘Jarvis’ of the enterprise if you will

As technology becomes cost-effective, AI has a stronger business case. In addition to its ability to uncover complex problems from data, the per head cost of some intelligent software robots is as little as one third the price of an offshore full-time employee and a fifth of an onshore full-time employee. As AI is propelled into a larger role in production, one needs to evaluate the implication of reduced human labor on the economy. The most recent debate on this topic was triggered when Bills Gates suggested that robots be taxed just like human workers and this earning be reinvested into reskilling of workers.

AI is improving the quality of service, even while keeping it affordable. We are still pushing the boundaries of AI and it definitely presents enterprises an opportunity to serve larger populations but while it solves one problem will AI lead to the emergence of others? This is the new question we need to address.