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10 artificial intelligence trends for 2020

There has been an exponential uptick in the number of platforms, applications and tools based on machine learning and artificial intelligence (AI) technologies in recent years. Here are 10 AI trends expected to dominate in 2020.

  1. Blockchain, internet of things and AI convergence – for AI to make a positive impact, it must be integrated with other technologies. For example, AI can work with the internet of things technologies to propel the development self-driving vehicles and work with blockchain technologies to address security, scalability and trust issues.
  2. AI-driven media and entertainment – AI is likely to penetrate the creative industries in 2020, especially given the high cost surrounding the economics of gaming and movie production.
  3. AI-powered cybersecurity systems – the sophistication and scale of cyberattacks are increasing at a faster rate, outpacing existing defensive measures. AI system will continue to play a significant role in detecting and managing these attacks.
  4. Disrupting traditional industries – AI is starting to penetrate almost every sphere of life and industry. It is clear that in a post-AI world, the success of enterprises will depend on their ability to prepare their human resources for disruption.
  5. Driving real-time consumer interactions – more and more marketing activities will become truly real-time, driven by AI’s ability to manage real-time interactions across multiple channels.
  6. Job creation – although AI is expected to eliminate 1.8 million jobs by 2020, 2.3 million are expected to be created. For the most part, AI-related job creation will result in more jobs with higher compensation rates.
  7. AI assistants – We already have popular assistants (e.g. Siri, Alexa, Cortana and Google Assistant), and an increasing number of companies will adopt intelligent assistants to handle basic tasks. Moving into 2020 and beyond, there will be more application of AI assistants.
  8. Biased data – over the last few years, some organizations have relied on machine learning models to assist them in critical decision-making (e.g. hiring decisions). Unfortunately, this trend might lead to biased data. For example, traditional employment data indicates that women are promoted less often than men, which might create a discriminatory AI-based application.
  9. Facial recognition – facial recognition is a trusted form of biometric authentication. Massive recent investments in this area are likely to lead to increased usage of precision facial recognition technology in 2020 and beyond.
  10. Privacy and policy – In 2020, we are likely to see an increased concern about the need to safeguard individual privacy.  Some of these concerns have been triggered by the latest developments in the AI sector.

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