2017 was all about the rise of AI and data science, or rather the hype around it; the fall of Hadoop; and robots beating humans at Poker and Go. It was also the year the data scientist became the most in-demand role in tech and many other industries. In 2018 there will continue to be a lot of noise about AI, but we are expecting a lot more action and real-world application. That last point is very much the theme of 2018 – helping businesses make real progress with the application of clever, useful data technology. So, what else can we see happening?
1) AI hype will continue to grow
In 2017 there was a huge amount of Hype around AI in all its various guises. In 2018 there is likely to be more of the same, but also an increased focus on repeatable and quantifiable results. This should mean smaller steps towards more realistic applications of the technology. Investment into the development of AI, particularly machine learning, is continuing apace. We are starting to see results appear beyond computers defeating humans at board games. Expect 2018 to see slow but steady progress as machine learning and neural network technologies take on more routine tasks.
2) Businesses will invest in more tangible machine learning strategies
We are going to see medium and large enterprises double their usage of machine learning by the end of 2018. Consequently, this means that their expenditure will also increase significantly from the $17 billion spent in 2017 to about $57.6 billion by the year 2021.
3) Unstructured data will become a thing of the past thanks to AI
We are going to see the cleansing of data sets increasingly handled by machines in 2018. Tasks that would ordinarily eat up processing time, such as managing the integration and cleansing of unstructured and structured data sets, will be handled by AI algorithms. This means that data operators will be able to focus more on those areas that both add the real value, and, crucially, can only be handled by humans right now – analysis and insight.
4) Academia and businesses will get closer to close the skills gap
A product of the global data skills gap will mean that businesses will be forced to work more closely with academic establishments to develop and access the talent that will drive growth. We have already witnessed Google buying-up data communities in 2017. Expect to see them, and others, go further in 2018.
5) Data literacy will become a priority across all aspects of business
Without a doubt, data literacy is more prevalent in today’s analytic economics than before. Researchers Gartner has discovered that organisations are looking to increase their data literacy by 80% by 2020. For this to be feasible, leading software companies will need to start offering these types of programs in 2018 and to develop a more structured approach to increasing data literacy.
6) Our interaction with machines will continue shifting towards voice
Just as Echo and Alexa snuck into our homes and became a viable part of our everyday lives, so conversational interfaces will become an almost indispensable technology in a business environment. In fact, one report suggests that about 20% of the firms will be looking to add interfaces that are voice enabled to their existing structures in 2018.
7) The blockchain hype will move beyond cryptocurrencies
We have AI to thank for improvements in integrating, processing, and managing distributed data. These new techniques and processes mean that less time is now spent on locating and validating data, allowing blockchain innovation to grow beyond cryptocurrencies. While this is in the early stages, 2018 will see innovations in areas such as analytics, data management, and in data authenticity, something that IBM has been exploring with its Watson AI.
8) Demand will continue to outstrip supply in data science and machine learning
Currently, data scientists, machine learning engineers, and big data engineers rank amongst the most searched-for jobs on LinkedIn. In five years, data scientists have grown six-fold, but demand continues to outstrip supply. Despite the best efforts of businesses, this will continue to be the case in 2018.
Overall we are looking forward to 2018 being a great year for data science, artificial intelligence and data scientists.