Artificial Intelligence trends in 2020

Artificial intelligence (AI) has made its way from University laboratories to the industry and found use cases in business over the last two decades and during this time, the main focus of AI in business has been in the data-driven perspective.

Artificial intelligence (AI) has made its way from University laboratories to the industry and found use cases in business over the last two decades and during this time, the main focus of AI in business has been in the data-driven perspective. 

From Data-driven to People-focussed

In 2020, in my opinion, AI will move dramatically towards achieving its focus on the people-focussed perspective. This perspective in designing solutions too needs data, but the overall focus of using AI will be for the direct benefit of commoners and not just big businesses or retail majors. This will liberate people from many mundane tasks they do in their daily life, just so to perform tasks that are more aligned to what they are as a person, and as a part of a society they live in. 

It may look like a gross generalization of the impact of AI, and just about any technology development in general, but this will be too good to be true in multiple areas of our normal living. So, instead of automating our tasks in life, we will start a new era of living a ‘fortified life’ or an ‘enhanced life’. A life in which most of the activities, events, moments, will be enhanced by AI, while we have wonderful opportunities to spend our time in the most productive way possible in our journey as human beings. 

Quoting Tal Gutman of Jiminy, “The AI solutions will work for me on a daily basis, as opposed to work on me”.

On a positive note, this means that AI tools will allow for greater individualization and a personal touch. But this will also pose a wide risk of security challenges to the users and companies.

Some of the key areas where AI will continue to impact our lives include, autonomous vehicles, deep fakes, small data and deep learning, voice and natural language processing, human and augmented intelligence, bias and explanation of the outcomes.

Many promising applications will emerge in medical intelligence and machine learning technologies and tools for software development, automatic learning of new tasks, education, learning and development, personalization and AI-driven customer experiences in our gadgets and VR/AR driven interactive terminals and new types of human-machine interfaces including, making it much easy to live and enjoy the finer moments of life.

Customer Service will be more attuned to live-up to its name in 2020. Moreover, the ability to automatically and instantly collect data from across multiple channels, analyse it and provide actionable insight will enable support agents to address customer inquiries rapidly, easily and accurately and arrive at a satisfactory issue resolution using AI and machine learning (ML) technologies.

Throughout 2020, we will see the focus around AI/ML shift from research into engineering, bringing an increased focus on managing the AI/ML lifecycle in production for internet-scale. There will be an increased focus on monitoring AI/ML pipelines, thus enabling to track the quality of prediction serving in production and perform optimized multi-model management in real time.

With the deepening of AI into embedded systems, we will see improvements in vehicles’ abilities to process visual data more efficiently, paving the way for autonomous vehicles in the future. For smart cities, AI-driven systems will assist crucial tasks such as real-time traffic monitoring, finding missing persons, and locating stolen vehicles.

In the area of Computational Linguistics, what we refer to as Natural Language Processing (NLP) in the Machine Learning world, unprecedented advances in enterprise knowledge graphs will enable context identification, content recommendation, and large-scale conversational systems to query any database with Human Language queries, essentially helping information workers to cope up with information sprawl. 

In the digital world, AI will help transform the digital workplace by augmenting and focusing human efforts and reducing cognitive burden by delivering information based on users’ current context.  

NLP combined with AI will increasingly make decisions that may be inscrutable to human observers, whether by analyzing stock data to make investment decisions, or parsing mountains of unstructured social media for broad sentiment analysis, ultimately helping businesses design and play their campaigns and advertisements in the user context, rather than the constructed context as it is done today.

In the fields of Data Engineering, Data Science and Analytics, the AI techniques with which we are familiar today — such as neural networks, event clustering, and regression — will be enhanced by less familiar techniques such as topological data analysis (TDA) and generative neural nets. TDA maps the geometric structure of datasets that are large, highly dimensional or noisy to detect patterns and uncover insights hitherto hidden in unknown dimensions and escaped our eyes due to our limited worldview of data analysis using linear algebraic methods. 

AI in FinTech in 2020

AI will increasingly impact the FinTech space positively with solutions that use predictive analytics for the following:

  • Real-time decision – making gained from insights and large data
  • Smart under-writing, client risk profiling, pricing and covering the ‘protection gap’ in the insurance industry
  • Personalized customer support 
  • Automated virtual financial assistants with human-like interaction
  • Virtual and augmented-reality based tools for wealth management plans
  • Ecosystem based solutions that enhance the interoperability of the existing solution landscape of financial institutions
  • Real-time insight management for Wealth Managers for targeted wealth advisory.

In my opinion, in 2020, AI systems will evolve to handle the key element of humanity – that is, emotions – in a well-informed manner. Businesses will look to unravel the valid and valuable use of AI in fact-based rationale and leverage the power of augmented reality and other digital technologies to create and manage emotional bonds through human interactions. 

Disclaimer: The views expressed in the article above are those of the authors' and do not necessarily represent or reflect the views of this publishing house