AI technology is redefining the geopolitical scenarios with its application.

AI is not one dimensional, solving over the range of issues and becoming part of a multitude of applications. AI today is defined by multidimensional and multi-applicable solutions, catering to a swarm of different meanings packed into them. Businesses are using Artificial Intelligence (AI) to define different things in many contexts based on the problems they solve.

AI has become an important technology for the economy today as AI is now able to define the geopolitical scenarios of the country. Going from the US elections to the Brexit referendum, the impact of AI is large and long. AI is infamously elusive to be defined completely, wherein it can be improved with just one word. We need to define ‘Intelligence’ first, a solution to bring automation into different systems.

The current AI technology is not one dimensional with metric and capability, and still one that can create an inference for human intelligence. In fact, we can call it intelligence that spans across domains with defined security rules, memory, language skills, planning, quantitative skills, abstract reasoning, design-making, emotional interference, creativity, which are some of them, and still, we are defining what can be added.

We are creating a copy of human intelligence with the machine, so the AI we are trying to develop is falling greater than only a single specific task or technology. Hence, AI is much more than a defined rule-based machine but comparable to human intelligence at the level of cognitive abilities. We have roughly defined AI beyond the single intelligence, a computing system that is capable of performing tasks that otherwise would require human intelligence.

However, many researchers believe that not having a universally accepted definition of AI has helped the domain in growing beyond the simple defined structure. Organizations are pushing for better and more developed AI, guided by a rough sense of direction and imperative to get on with it. Characterizing the AI depends on the credit one that is willingly provided by synthesized software and hardware that function with the intelligence of human perception.

Covering the multidimensional spectrum, it’s still an industry under making. As we develop more machines, bring more algorithms about objects’ definition, we are still lurking in the darkness for AI’s definition.  An important aspect when businesses are looking to develop AI technology is that it’s a moving target combined with an AI effect. Though we still don’t define this technology, it’s setting the trend of disrupting the complete world order with its closed applicability.

Here are three aspects that will be defining the AI application:

1. Smaller economies or emerging economies have talent in abundance. With better utilization for the already available pool of resources, they would be challenging the larger ones.

2. According to Tortoise Intelligence, AI would be radically reshaping geopolitics.

3. Centralized AI strategy works better than the distributed one, and China will doinate with that strategy.

AI is shaking up the economic growth for many businesses, allowing many of the small businesses to stand out in the current competitive landscape. The currently established metrics to calculate the economic success are greatly driven by the number of GDP scale, but according to a new report, most economic forums are failing to understand that in an AI-driven world, the consumers will still be questioned.

The economies that make the right investment decisions are currently more equipped to provide their population and business with technology and even satisfy the training needs for AI. Currently, in the AI race, both the countries, the US and China, are looking to dominate the AI race, but many of the smaller nations are also looking to gain edge.

Experts believe that AI could be setting the tone for the fourth Industrial Revolution that could completely change the world order of economic powerhouse. The forum established the center for the fourth Industrial Revolution Network in 2017 to ensure that new and emerging technology will assist or not harm humanity in the future. Headquartered in San Francisco, the network launched centers in China, Japan, and India in 2018 and is rapidly establishing locally-run affiliate centers in many countries around the world.

Tortoise Intelligence, an investigative journalism forum, calculated the AI investment made by a group of 54 countries. The US spends close to $54,128 million, while in the second position, we have the closest competitor China, close to $12,499 million. The major difference that separates both countries is that most of the investment in the US is from private businesses, while in China, it is centralized by the government. The gain China has got is over the period of the past three years is overwhelming many of the governments around the world.

The government-driven industrial policies have committed to AI spending for China that is soon to eclipse the US. According to Tortoise, the value of China’s AI spending plan is currently over one-and-a-half times greater than every other country in the world, all combined while the country spends more than the US on AI research.

AI has the potential to add close to 16% or about $13 trillion by 2030 to current global economic output, with an average contribution to productivity growth of about 1.2% between 2018 to 2030, according to 2018 report by the McKinsey Global Institute on the impact of AI on the world economy. According to the report, if the impact of AI is compared with any other general-purpose technology through history, we can see how technology has shaped the generation.  The introduction of the steam engine boosted productivity in the 1800s by an estimated 0.3%, impact from robots during the 1900s around 0.4%, and the spread of IT during the 2000s by 0.6%.

The McKinsey report is based on the simulation model of the impact of AI on the country, sector, company, and even at the worker level. The general adoption channel observed includes- computer vision, virtual assistants, RPA (Robotic Process Adoption), natural language, and advanced machine learning. Data sources include approximately 3,000 firms in 14 different sectors.

Even according to a recent report from PwC, AI technologies and applications will increase the GDP by up to 14%.

Below are some of the key findings from the report combined:

1. There will be a significant cost associated with managing labor market transitions, especially if the workers have been left behind by the AI technologies. It could even reduce the gross impact of AI by about 10 percentage points.

2. The economic impact will emerge gradually and visible only over time. McKinsey’s model showed that the AI marketplace adoption is likely followed by a typical S curve pattern with a slow adoption rate with a steep adoption rate as the technology matures, with firms learning how to deeply better.

3. AI is set to widen the gap between the counties, companies, and workers. The US and China are leading when it comes to the adoption of AI. Many countries that don’t have the investment or infrastructure for the development of digital infrastructure risk falling behind.

4. While the adoption rate among the businesses will still mostly vary, with frontrunners comprising about 10% of businesses. Followers that will comprise 20–30 % of firms are more cautious type. Laggards will be the last group consisting of about 60–70% of firms that are not seriously investing in AI.

The wide gap in technology might be pushing some new innovators to take advantage of the gap. We have seen a few major organizations pushing some economies toward the betterment of AI technology.

A report shared by the European Parliamentary Research Service authored by Marcin Szczepański said that the patents have been on the rise by 6% averagely each year between 2010 and 2015. The growth rate of patents is higher in AI compared to other sector patents.

The countries that have been leading the bandwagon for the research are from Japan, South Korea, and the US that accounted for two-thirds of the AI-related patent applications. China, Chinese Taipei, and South Korea have recorded an exponential increase in the number of AI patents compared to past numbers. The EU member states contributed 12% of the total AI-related invention for the period of 2010–15, and a decrease of 19% was recorded compared to the previous decade.

Conclusion
AI tech is moving toward data tech, with a focus on analytics and algorithm-based technology. With IoT and 5G assisting in data gathering over the next decade, the shift to more realistic applicable AI technology will happen.  Businesses need to be cautious in managing investments and technology development. To know more about AI technology, download our latest whitepapers on AI .