Top 8 Artificial Intelligence Trends in 2020


The term Artificial Intelligence or AI has been the main buzzword of the technology field in the past couple of years or so. This is mainly due to the recent rapid developments in machine learning and deep learning in recent years.

Now, artificial intelligence is one of the fastest-growing industries, and at the same time, the most unpredictable.) AI-powered deepfake, for example, is one of the least predictable AI implementations in recent years.  

So, predicting future AI trends in 2020 and onwards is arguably one of the most challenging tasks with the unpredictable nature of the field. Yet, based on our research and discussions with scientists and experts in the AI and machine learning industries, here’s our prediction for artificial intelligence trends in 2020:

1. More Efficient Data Usage

Data size is currently one of the key challenges in AI development. Most of the recent and practical AI implementations are based on machine learning and deep learning, and the thing is, deep learning is extremely data-hungry

The deep learning process involves exposing the AI program to a very big amount of data, where the data will then train and validate the AI’s accuracy and capability. Thus, for AI developers, getting a massive amount of appropriate data can be very challenging, both volume-wise and data type-wise.

To tackle this issue, various parties are currently working on developing various data synthesis methods, so we can use the data that is already collected and synthesize it to create more data. Recent advancements in GAN (Generative Adversarial Networks), for example, have allowed such data synthesis activity. 

In 2020 and onwards, we may see various breakthroughs in data synthesis methodologies to tackle this issue of data volume requirement.

2. AI in Economic, Military, and Politics

It’s no secret that that AI has been a major topic in military and economic security discussions. On the one hand, AI technologies open up many different possibilities in so many different fields. On the other hand, it’s quite obvious that AI technologies will be potential security threats on an international scale.

It’s also quite possible that artificial intelligence will shift the balance of power, which can further destabilize global security. As a result, governments are already investing heavily in AI developments and existing AI technologies. China, for example, has invested more than $140 billion. 

AI-related talents will also be in-demand throughout 2020 and onwards due to these geopolitical issues. 

3. AI Trustability and Explainability 

Ethics surrounding AI implementations and risk management (related to geopolitical issues above) have been the major emphasis throughout 2019. 2020, on the other hand, will be the year of AI’s explainability and trustability.

Explainability, however, is a fairly new concept, which essentially means, the ability to explain what causes the AI-based decisions, but it’s now becoming increasingly known among many tech practitioners and users. Many big companies, including the giants Google and Microsoft, have also taken their steps in ensuring their AI developments to be more conformant to current standards of ethics. 

AI trust will be a huge focus in 2020 and also for the years to come, with more technologies and developments focused on providing solutions for trustability.

4. Improved Artificial Neural Networks

Deep learning relies on the usage of Artificial Neural Network (ANN) to improve the traditional machine learning process by mimicking the human neuron system. Many advancements in AI implementations throughout 2019 are made possible by ANNs.

In 2020, we can expect the neural network architectures to grow even bigger and deeper, increasing their capability in imitating humans in data analysis and produce more accurate results. New technologies and methodologies are also being developed to improve the overall efficiency of ANNs, so we can expect to see power-efficient artificial networks that can run on mobile devices to process real-time data.

Improvements in ANNs are not solely focused on performance and efficiency, but also on the issue of reliability and data bias, related to explainability as discussed on the previous point.  

5. AI for AI Development

As we have established above, one of the key issues we have in the AI field is R&D: it takes a long time to develop an AI, and even after it’s developed, it will take another long time and a massive amount of data to train and validate the AI (as discussed in point #2). 

One of the potential solutions for this issue is using AI to help automate some—if not all— the processes of developing, training, and operating AI models. We can expect to see significant new innovations in this area, and so AI development will be more accessible to a wider audience. 

In early 2019, for example, IBM launched AutoAI, a platform designed to automate AI model development and data preparation. Similarly, Google launched Cloud AutoML (ML stands for Machine Learning), which is designed to simplify and automate the process of machine learning model developments.  

We can expect more players, big and small, to enter the AI development automation industry in this next decade.

6. AI Will Finally Change How We Work

It’s no secret that one of the biggest controversies in AI technology is whether or not it will take our job. In 2020 as the start of the new decade, we can finally find out the answer as AI will continue to make its impact in the workplace. 

In general, however, yes, AI will completely replace some of the tasks that used to be our jobs, but at the same time will open up new job opportunities and will create completely new tasks through automation and deep analytics. 

According to the latest research data from MIT-IBM Watson AI Lab in October 2019, AI will increasingly replace jobs that involve repetitive tasks and robust calculations, such as scheduling, automation, data input, and so on. However, AI won’t directly impact jobs that require specific skill requirements and especially creative skillsets, such as design, strategic, and managerial jobs. 

In 2020 and onwards, we can expect more workers to experience these effects, as more companies will adopt AI technologies to assist in various job roles. Human employees, on the other hand, should focus on expanding their expertise and skills, as well as hone their creativity. 

7. Widespread AI Implementation in Manufacturing

More AI technologies will be implemented in the manufacturing industry in 2020 and throughout the next decade. 

One of the biggest challenges in manufacturing in the past few decades is quality control, which in most cases, requires the help of expert human supervision. Even then, the most experienced QC managers can struggle with inspecting each individual while also meeting the demanding deadlines of the fast-paced industry.

AI solutions and technologies, on the other hand, are faster and more accurate in inspection than humans ever will be, while at the same time can free the human workers from exposure to hazardous tasks. 

Edge computing technologies also have their part in enabling the implementations of AI solutions in the manufacturing industries. Before edge computing, manufacturers are forced to invest in cloud data servers, which can be extremely expensive due to the size of the manufacturing operation. Edge network technologies, on the other hand, can allow a factory to run AI models without linking the whole operation to the cloud.

Edge computing can allow manufacturers to generate (and potentially, synthesize) data while also reducing the massive costs that are often tied to cloud computing as well as lowering latency.

8. AI To Allow Cheaper and More Precise Healthcare

Many experts are suggesting that the key impact of AI technologies in 2020 will be how it will transform healthcare systems and processes. AI solutions are expected to not only help reduce the currently very expensive healthcare cost, but also to improve the generated values for both patients and healthcare professionals alike. 

One of the key areas where AI can help healthcare workflows is data collection and processing.  The healthcare industry often involves a massive amount of data that must be processed in real-time: health records, equipment usage, staffing, department admissions, and so on. AI solutions can help collect and analyze a massive amount of data with different types in real-time, and also automate some of the processes.

In 2020 and onwards, we can expect AI implementations in healthcare to include applications like optimized and automated scheduling, reporting to various departments and individuals, automated equipment validation and settings, services personalizations, and other functions that are mainly related to automation and deep analytics.

Complex and often wasteful administration process paired with over- (or under-) diagnosis are two of the most common reasons for inefficient healthcare workflow, and AI solutions can significantly help in these key areas. 

End Words

Artificial Intelligence is, on the one hand, the fastest-growing field in technology with a wide range of possible applications and implementations. On the other hand, it is also the most unpredictable field with literally countless potential implementations. 

With that being said, the 8 predictions we have shared above are among the most certain and important ones and can be a solid foundation if you are aiming to invest or work in the field of artificial intelligence in 2020. 

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