A Closer Look at the the AI Industry In 2020
Sun, April 18, 2021

A Closer Look at the the AI Industry In 2020

Artificial intelligence is one of the fastest-moving and least predictable fields, according to Ben Dickson of The Next Web (TNW), a platform dedicated to new technology and start-up companies in Europe / Photo by: Kittipong Jirasukhanont via 123RF

 

Artificial intelligence is one of the fastest-moving and least predictable fields, according to Ben Dickson of The Next Web (TNW), a platform dedicated to new technology and start-up companies in Europe. A few years ago, deepfakes, AI-powered machine translation, and bots that can play the most complicated games were inconceivable. Since then, these have become increasingly common in our everyday lives. 

AI offers both benefits and risks to human beings, said Christopher McFadden of Interesting Engineering, a technology and science news platform. The technology is still in its infancy but it is already utilized in interesting ways. Despite AI being unpredictable, let’s try to see what AI is in store for us. 

 

Fascinating Statistics on AI 

Since AI has become a part of our society, don’t be surprised when worldwide data will grow 61% to 175 zettabytes by 2025, as stated by IDC (International Data Corporation), a global market intelligence firm, reported Giselle Abramovich on CMO, a website on technology and market trends. 

Worldwide spending on AI is projected to reach $35.8 billion in 2019, a 44% increase from 2018. This will double to more than $79.2 billion in 2022 with a CAGR of 38% over the 2018-2022 forecast period. We will see the most investment in certain AI use cases such as automated customer service agents ($4.5 billion worldwide), sales process recommendation and automation ($2.7 billion), and automated threat intelligence and prevention systems ($2.7 billion). 

AI Trends You Should Watch for in 2020

1. The Geopolitics of AI 

Ishan Manaktala, CEO of Symphony AyasdiAI, noted, “AI will remain a top national military and economic security issue in 2020 and beyond.” In fact, governments are investing in AI to stay competitive. For example, China has invested more than $140 billion while the UK, France, and the rest of Europe have dedicated more than $25 billion into AI programs. While late on the AI bandwagon, the US spent about $2 billion on AI in 2019 and is expected to invest more than $4 billion in 2020. 

Manaktala stated, “But experts urge more investment, warning that the US is still behind.” According to a November 2019 survey by the National Security Commission on Artificial Intelligence, China is likely to surpass the US in research and development spending in the next decade. The report outlined five points, namely invest in AI R&D, apply AI to national security missions, train and recruit AI professionals, safeguard US technology advances, and spearhead global coordination. 

2. Facial Recognition Will Become More Ubiquitous 

Facial recognition is being adopted by private and public organizations for various applications such as surveillance. AI-enabled surveillance is already employed in many airports all over the globe, and it is even utilized in law enforcement. 

AI is leveraged to recognize people and track their locations and behaviors. Some programs in development are capable of analyzing an individual’s gait and heartbeat. Valuing at $4.6 billion, facial recognition will not be going away as its annual revenue growth rate is projected to increase by more than 20% in 2020. This growth is attributed to the improved accuracy in facial recognition technology, market intelligence platform Visiongain said. 

3. Workforce Upskilling and Hiring AI Professionals

Gartner, an IT service management company, found that 37% of enterprises have employed AI in some form, a 270% increase over the last four years. As more AI projects are developed, data literacy is a crucial skill for employees outside traditional data teams, argued Roger Magoulas of IT news website IT Pro Portal. Gartner also stated that 80% of organizations will formulate internal data literacy initiatives to upskill their workforce by 2020.  

Training the employees is a continuous endeavor, but in order for business owners to succeed in employing AI and machine learning, they need to employ a holistic approach in retaining their workforces. This is a difficult approach, but it is actually the most rewarding as this allows employees to gain a better picture of the successful implementation of AI and AI solutions. 

Interestingly, retraining employees also entails rethinking diversity. Since reinforcing the significant role of diversity is important in detecting bias, promoting diversity becomes a critical aspect of businesses that are looking to implement useful AI models and related technologies. AI will augment human tasks. Hence, incorporating the human aspect and fostering inclusivity will lead to widespread success and acceptance. 

On the other hand, it is also important for businesses to hire AI professionals. In the last two years, demand for AI talent has doubled, but talent remains to be in short supply, unfortunately, according to capital market company MMC Ventures. With roles available for every AI professional, 60% of AI talent is recruited by technology and financial service companies. 

4. Roboethics

Developers will be more pressured to preserve the ethics of their work. It could be developing an ethical framework on how humans should and should not use AI. The framework can also encapsulate how AI itself should act morally and ethically. The main concern is preventing humans from using AI to cause harm or even preventing AI units from harming humans in the future. 

We can’t deny the significant role of AI in business and in our lives. The inevitability of technological advances will force us to adapt to the ever-changing nature of society.

Gartner, an IT service management company, found that 37% of enterprises have employed AI in some form, a 270% increase over the last four years. As more AI projects are developed, data literacy is a crucial skill for employees outside traditional data teams / Photo by: everythingpossible via 123RF