The first step to implementing AI is finding applicable cases and then working with various state departments and entities to develop rules, regulations and policy. In 2016, Oman launched a $200 million investment fund dedicated to tech start-ups in the Middle East and across the world.
Furthermore, the Information Technology Authority (ITA) has put increasing importance on AI, realising its significance to the country’s future and is currently working on a proof of concept using AI technology with the Ministry of Health.
Successful AI use cases
One of the biggest beneficiaries of AI technology is security. Here in the region, AI has tremendous potential when it comes to security – and the technology is already being implemented for image processing, facial recognition, predictive analytics, and so on.
The customer service industry in the region is also increasingly turning to AI to manage its growing needs, and AI is being used quite extensively in consumer applications. Mobile apps are now designed to enable seamless government service delivery and we are seeing chatbots used across retail, banking, government services.
AI is making it possible to deliver more personalised experiences — and with the advent of chatbots, we are seeing a level of disruption that we have not seen before in the industry. This will continue to drive customer service across government services and the private sector.
Healthcare is going to be massively impacted by AI in the future as the industry moves away from traditional methods and uses complex algorithms and software to assist doctors in patient diagnosis. To illustrate, the first mapping of the human genome cost an estimated $3bn and took roughly 15 years to achieve. Today, it costs $1,000 to map the human genome for an individual in mere hours. That’s a sea change in a remarkably short span of time, unlocking opportunities to tailor medicine for individuals, including precision medicine, drug development and diagnostic imagery.
Transportation is another industry that is on the precipice of disruption, thanks to AI. For example, long haul autonomous trucks in the US are poised to disrupt the logistics industry.
When it comes to energy and R&D, technology and algorithms are enabling precision drilling, reservoir management and driving safety and production. R&D has historically been an expensive process, but AI has the ability to churn large amounts of data in a short span of time, which can substantially reduce costs for various industries. Another emerging technology that has the potential to disrupt the oil and gas sector is Augmented Reality (AR). This technology has many benefits, from impacting something as simple as off-shore repairs, to improving worker safety.
Innovation related to language will be a huge enabler for engaging and interacting with people. Media and content as a business is already being shaped by AI and the next stage is to leverage this for language translation. The language barrier could potentially be one of the biggest challenges impeding customer service delivery, and AI opens up new apps to overcome this and engage with the public.
While the use cases are great, AI has become an elastic word today. Everyone is talking about AI without fully understanding what it means for their business. Companies that are serious about taking up AI must focus on two things – the business case benefits and the use case benefits and they must adopt a nimble and phased approach to start building momentum.
The best way is to start with implementing AI on a small scale and build it as you go along. It is also very important to think about AI in a broad context with Machine Learning and Deep Learning at its core. Not all problems can be solved by either Machine Learning or Deep Learning. Understanding the use case and then employing the appropriate tools is critical for success.
Implementing AI also calls for a massive cultural transformation. By this, we mean that the technology needs to be made more native, so for example, chatbots needs to be more natural and far more human centred.
Understandably, one of the biggest challenges to implementing AI is the perceived threat of redundancy or job loss. But governments and the private sector need to understand the nature of the labour market, and think about how they will shape it for the future. AI should be implemented in a way that repurposes the energy in the labour market rather than making it redundant.
Another challenge with implementing AI is in relation to transparency and bias. When you apply algorithms and deep learning, you don’t always know why machines make the decisions they do. With AI, we will also need to figure out how to regulate bias e.g. in autonomous applications, there could be issues when it comes to saving lives in case of a collision or denial of care or benefits in healthcare.
The legal ramifications could also vary from one country to the other. So for example, how an algorithm in an autonomous vehicle makes a decision to save a life in one country based on certain criteria, could be different from another. The geographical boundaries of these challenges create a complexity that we are not aware of yet.
Another critical challenge is scaling up AI, anyone can do small scale AI pilots, but transforming those successes into enterprise-wide solutions requires hard work, including integrating transformation, strategy, technology, data and analytics successfully.
We also need to be mindful of the sheer volume of data that is being generated, which has become one of the most valuable assets for organisations today. In the last two years alone, we generated 90 per cent of the data in the world.
The evolution of what we can achieve and do with data is exponential and we are underestimating the breadth and pace at which AI is going to unfold in the future.
As the GCC moves away from an oil-reliant economy, AI is a very promising growth area. It will be important for countries to continue to invest in AI, by increasing adoption across various organisations, upskilling its talent base and continue working on the right enablers, to transform the way we live and work.
Source Link: www.omanobserver.om