Machine Learning and Artificial Intelligence (AI) trends in 2019 proved that 2019 was an essential year for both AI and ML, as both ML and AI became more and more mainstream in international businesses and their unseen potentials got rapidly manifested in real-life situations.

 

Let’s see AI and ML trends will be in 2020:

 

According to Forrester by 2020, “businesses that are using artificial intelligence (AI) and machine learning technology will gain $1.2 trillion annually from their market base.”

 

Business experts say artificial intelligence or AI is going to create nearly 2.3 million jobs and do away with 1.8 million. The developed countries will see 20% of their population using AI assistants for everyday work this year. In another interesting development the upcoming AI projects which have “built-in transparency” are going to get enterprise funding by the end of 2022. Again, by 2024, shortage of data scientists will cease to be a barrier for enterprise Data Science (DS) or machine learning (ML) implementation. While cloud technology provides “agility to business processes,” AI and ML technologies can collectively convert business results.

 

In 2020, AI solutions will continue to be implemented as a mainstream technology to boost business efficiency and productivity. UiPath, Informatica, or Pegasystems — all of these innovative decision-support tech-platforms can explore AI and ML applications in order to control creation, dissemination, and sharing of analytics content.

 

This year, cloud service providers are expected to offer MLaaS to businesses with no on-premise Data Management facilities. Renowned MLaaS companies, including Amazon, IBM, Microsoft, and Google, are already offering MLaaS services to enterprises that do not have in-house ML programs. This year, the most hunted ML services will be natural language processing (NLP), predictive analysis, and data visualization.

 

Similar to MLaaS, combined AI platforms having diverse features and potentials will emerge as services by third-party providers this year.

 

AI up-skilling trend which started last year will continue all through 2020. Up-skilling the existing employees with AI skills will be a key business strategy of the new decade. This will create many more citizen data scientists, citizen developers with power AI skills, and a niche band of professional data scientists and data engineers.

 

This year, the Data Science job positions will be re-structured according to the above mentioned alignment of skills and technical expertise. According to industry experts, right from 2020, AI is going to create additional jobs in sectors which will be taken over by it. The existing gap in the job market for professional data scientists needs to be filled by initiating Data Science courses and DS apprenticeship programs. 2020 will see launch of numerous such courses.

 

Trust deficit in AI is going to be answered by ethical and well-governed Data Science practices. Also the present prejudices and interpretability owes regarding AI will need to be handled by means of Data Governance, Data Quality, and Data Stewardship best practices.

 

Embedded analytics having built-in machine learning models are going to be a mainstream potential of all business intelligence platforms this year. In effect, all major BI companies are now in competition to implement embedded analytics capability in their systems, so that they can get a share of the 2020 BI market pie.

 

AI and natural language processing (NLP) will collectively aid in creation of voice-activated assistants, akin to Alexa or Siri. These helpful assistants will effectively transcribe human language into data which will help in further analysis. AI, ML, and NLP are going to offer solutions for interacting with business data organically. With this happening, enterprises will no longer need to depend on data scientists and advanced data analytics platforms as augmented analytics will help AI models to interact with data directly and provide key, effective insights to business users.

 

ML, In 2020, AI, and NLP are going to be more and more inexpensive and readily available for companies of all sizes. This happened due to the extensive commercialization of the applications. The budget enterprises will not need to worry of investing in on-premise data centers.

 

Companies building business apps will continue to thrive through 2020. However, the developers must keep in mind that great ideas alone will not help develop great apps and ideas will have to be shared with, nurtured and guided by experienced business and technology gurus in order to be converted into commercially viable products.