Published on August 8th, 2019 | by Bibhuranjan0
Prominent challenges that Hinder AI Adoption in Developing Nations
Much of the world today enjoys the many benefits of AI and its related functions. There is no question or doubt that this technology is here to stay and grow exponentially as our technological know-how increases while experimenting on the field.
While the deployment of AI across the cities and nations was surely slow to begin with, with time, it got steady and now its more like a spreading wildfire. There is simply no escaping the benefits of automation technologies to accelerate tasks and get more productive.
While all of it sounds great on paper, the magnitude of adoption for AI and its related technologies remains severely limited in many parts of the world, especially in 3rd world nations that are still under developed.
Prominent hindrances in adopting AI
AI technologies at its core requires data to operate. The more data that is fed into the machine, the more we can get it to automate. That is easier said than done and it is especially difficult in nations like Africa, parts of Middle East and even Latin America where growth still remains lacklustre and technology adoption isn’t as high. This can pose challenges in the long run as Governing bodies that aren’t infrastructurally equipped with AI technologies lag a lot behind the world development curve.
That being said, the lack of its adoption can be attributed to a few reasons:
1. Bottlenecks in Communications and Connectivity
This is a very simple and straightforward reason, why AI isn’t being mass adopted in a said country. In essence, if a nation suffers from a lack of communication, in the form of reduced cellular and internet connectivity, it can lead to poor AI integration and functionality in the nation. The reason here is that AI feeds on data, and the more it has to work with, the better it is when eventually deployed. A lacklustre communications infrastructure could mean that the nation could be lacking basic AI related facilities like AI Chatbot, AI based data collection or even AI based Localisation services.
2. The Nation Suffers from a Lack of Funds
This is another reason as to why AI or automation might not be a viable option for many nations. There is a huge deficit for surplus funds in a lot of developing countries. And while most of these poor nations get regular funds via entities like the World Bank and EU continues to aid these places with funding, the issue remains that the country itself is unable to sustain its economy viably and therefore, venturing into AI based operations might not be the most economical route.
3. Lack of AI based Infrastructure
This type of issue might not present itself on the surface but it is a deep-rooted problem that needs a lot of work to get sorted. According to a study by Accenture even moderately developed nations like South Africa, which on paper has the ingredients, for a full fledged AI network, isn’t ready for it because the nations existing infrastructure like schools, medical, Office Networks are in a very poor state and cannot viably sustain any form of AI automation. On top of that, skilled personnel in this field is very low too, which means if any automation system is put in place, most of the workforce is going to be outsourced.
4. Internal Pressure
There is a very common theory that Automation will eventually lead to reduction in human jobs. While that is not entirely untrue, it is only a fraction of the whole picture. But that is enough to cause a panic among developing nations that suffer from poverty and where people live with a sense of job insecurity. In such places, the Govt can be forced to stay away from implementing any real form of AI Automation as it can be used as a propaganda to displace the ruling Govt from the country. This is unfortunate but it can be widely seen in a lot of Under-Developed and Developing Nations, that favour traditional ways of working.
5. Not enough Initiative by the Working Government
While Internal Pressure can be a result of masses not being in favour, the inverse to this is a Government that has no initiative for AI based projects at all and traditional methods of getting work done is working in their favour for reasons unknown. Now the implications of this practice are fairly adverse, considering that by choosing to remain behind the technological curve they are not just pushing the country into the dark ages, but also limiting the options for its citizens to venture out from within the country.
6. Non-Future Proof IT Infrastructure
While the adoption rate for newer technologies might be high such nations, it can still be AI incompatible. These nations, that are generally at the forefront of being considered as “Developing”, and while it attracts new companies, for investment and development, they still don’t get the latest advancements in AI based automation technologies quite as quickly because the existing infrastructure isn’t a viable option. Luckily though, such nations generally have progressive Govt’s that are willing to invest in advanced technologies and infrastructure development, so the persisting issues can be resolved in the future.
7. Excessive Bureaucracy and Technological Theft
This is a fairly unique challenge when it comes to AI based applications. The issue here isn’t really lack of funds or infrastructure but rather making it difficult for companies to implement the AI infrastructure in a way that is viable for them because of certain Govt. rules or failure to regulate the market. This lack of market regulation and Govt. bureaucracy can also cause intellectual property theft by local companies which can cause losses to the parent companies. This can later discourage any further advances in the field to be shared with the same country, leading to technological stagnation.
So by now you have a fairly vague idea of how various reasons can lead to lack in adoption for AI and other automation systems. While are some of these are a result of poor development and financial restrictions, some of them are by choice or are consequential of their respective ruling bodies.