Artificial intelligence: What changed in 2018 and what to expect in 2019
In the artificial intelligence and machine learning space, 2019 will see the rise of the intelligent application
Artificial intelligence (AI) is one of those technologies that excites the public and business imagination alike. Long since a favourite theme in science-fiction, it is now gaining traction in everyday practical scenarios.
In 2018, we saw a considerable rise in the adoption of AI around the world and across industries, with businesses using it to improve operations, generate new innovations and boost customer experience.
With financial services, telecoms and high tech leading the way in bringing AI into the mainstream, and other areas such as automotive, healthcare, energy and retail also embracing it, we expect the rapid growth of AI to continue in 2019 as companies strive to get the most value and competitive advantage from the data they capture. Let’s take a look at what’s been powering the rise of AI recently and what might be around the corner.
Data is the fuel for AI. As data collection, analysis and storage abilities dramatically improved over recent years, most companies found themselves with a huge potential resource and yet under-equipped to wrestle with such high volumes of information.
In 2018, that started to change, as the people skills made headway in catching up with the technology. There remains a lot of complexity around how data is handled and used, but businesses are starting to see a deeper understanding of the specific skills needed to help companies bear fruit from data, and how these can be mapped onto ‘personas’ they can train up, or recruit.
Businesses are steadily learning how data scientists and AI developers work differently from traditional app developers, the tools they need, and how to bring them into app dev teams cohesively.
For vendors in this space, the challenge is to make AI more easily accessible for all developers. Some are building machine learning frameworks to help organisations apply AI across use cases.
In 2019, vendors and enterprises alike need to continue to broaden their skill set, training existing developers and bringing new data scientists on board. To target the shortage of data scientists (and other data worker personas) at its roots, as a society we need to engage and inspire young people to boost demand in the education system, as well as supply that education. With a continued push expected this year and beyond, AI can fulfil its potential ‘superpower’ status for developers, helping them tap rich new sources of innovation.
One use case that has become more prevalent in the last twelve months is chatbots. Chatbots’ increase in popularity stems from businesses’ desire to give users the same experience online as they would get in-store – be they retail banking customers, healthcare patients, retail shoppers, or whoever else.
Chatbots are great because they can respond very quickly to customers and deliver personalised care by taking advantage of data analysis and algorithms to determine the category a user falls into.
