AI Special: Solving the world's toughest problems

Artificial intelligence (AI) has without doubt been the single most transformative force in the technology sector over the past five years. Recent studies suggest that one in 10 enterprise companies uses 10 AI applications or more. This could be anything from chatbots to cyber threat detection and credit checking to product recommendation engines.

Why has AI become so relevant today? The answer is hidden in the data. Armed with AI, companies now have the ability to process massive datasets at speed with little human intervention to constantly discover hidden insights and provide better solutions to the world’s problems. If ‘fail fast’ is the mantra of every aspiring tech entrepreneur, AI is their weapon of choice.

Critically, in recent years, the addressable market for AI solutions has ballooned. As per the International Data Corporation, worldwide revenues for the AI market, including software, hardware and services, is forecast to be $327.5 billion, and expected to grow at a CAGR of 17 percent to $554.3 billion by 2024. The acceleration of cloud computing, reduction in the cost of outsourcing data storage and the increased access to high-speed internet services have converged to create a ready B2B & B2C customer base for AI innovations. If high-quality data can be harnessed, then smart AI can make sense of it.

In this article, we want to highlight three areas where AI is taking on some of the world’s toughest challenges and helping us solve problems that have been too complex to have been solved with traditional approaches.

1. Proactive health care systems

It would be fair to state that until the early 2000s, health care as an industry was largely driven by reactive actions of individuals when their health deteriorated. The decade starting 2010 witnessed a significant change where technology permeated health care to usher in more precision, prevention and wellness transitioning from reactive to a more proactive health care system. The coming decade will be defining in terms of AI leveraging reams of data to smartly monitor health, improve diagnosis and clinical outcomes, introduce process efficiencies while declining health care costs.

We expect to witness AI’s impact on improving standard of care through AI-enabled diagnostic systems enabling providers and labs to standardise scan reports and remove variability in possible interpretations. Further, predictive analytics is seen to be increasingly deployed in critical care or step-down care to prevent code blue events or readmission of post-surgery patients. In health care-resource starved countries like many in Asia, critical health care resources can be used to remotely secure adequate clinical data of a patient, leverage AI to analyse the data on cloud and manage patients as effectively as one would in person. This would allow patients in remote locations to access the best doctors remotely while the doctors/nurses are able to use AI to get standardised data-driven solutions to manage patients.

2. Future of learning

The human mind is an amazing act of creation. There are about 100 billion neurons where each is connected to approximately 15,000 other neurons via synapses. Whenever our brain perceives any information, the neurons get excited and chemically transmit electrical signals to other neurons via synapses. This beautiful orchestra can be broadly defined as the process of learning.

Thus, it is important to understand that any kind of understanding of the process of effective education is incomplete without properly understanding the neurological or cognitive process happening in our brains. Unfortunately, the last few centuries of work in education has focussed on stimuli such as content funnelled by the external world. Only recently, people have started focusing on cognitive processes such as importance of focus, retrieval practice, spaced practice, interspacing which can be collectively bundled under the title ‘cognitive personalisation’.

Essentially cognitive personalisation is understanding each learner’s cognitive abilities and customising the delivery of information accordingly to get the best learning outcomes. This has the potential to revolutionise the way we have been learning since ages. However, the challenge is the huge data that has to be analysed in real time to create pedagogical inputs best suited for each individual. This is where AI comes into action—proper data sets, powered with unique intelligent algorithms collectively called AI, have the power to transform the world.

AI-based learning tools today are focusing on personalised learning solutions and intelligent content distribution—that is the future of learning via AI.

3. Fight financial crime

AI is giving us a boost in the arm in solving some of the largest and most complex financing problems. Financial services institutions are having to reimagine their approach to prevent money laundering. An estimated $2 trillion is laundered each year and banks simply haven’t kept pace. Despite spending $180 billion on prevention, only $40 billion of the laundered money has been caught or reported and less than $5 billion of that is actually recovered. Beyond the financial damage caused, the reputational and human impact can be devastating.

Why was the return so bad? Because the AML (Anti-Money Laundering) strategies of the traditional banks were rules-based, human-powered and siloed from each other. Simply put, the innovation among the money launderers far outpaced the ability of the banks to amend their rules and apply them.

Innovative companies like Tookitaki, a star in Jungle’s portfolio and the ‘Technology Pioneer’ award winner at the World Economic Forum, have embraced AI and applied levels of creativity and innovation that the traditional banks are simply not set up to deliver. The team at Tookitaki saw that AI could far outpace people in its ability to process large volumes of data, note irregularities and flag potential instances of fraud, with greater accuracy and within the boundaries of regulatory compliance.

AI-powered business ideas are every day, but real game changers are rare. In our experience, the best ideas don’t start with the tech, they start with the problem. Is there a real problem to solve, is the total addressable market big enough and is there enough data to fuel AI innovation that goes beyond the expected?

We are excited to see the next generation of founders in Emerging Asia reject the status quo and use AI to take on the challenges that many giants of industry have shied away from.

The writer is founding partner, Jungle Ventures