BM’s Global AI Adoption Index reveals that almost a third of all the world’s companies are already using some forms of artificial intelligence (AI), with over 40 per cent currently weighing up whether to do so. The figures and forecasts from the Everest Group paint an even starker picture, with the market research firm expecting global spending on AI services to hit USD 95 billion in 2024, compared with just USD 25 billion in 2019. What is leading CIOs and CEOs to invest so much so fast in automation and AI?
The main reasons are cost pressure and process speed. By investing in AI, companies are hoping above all to make their processes more efficient and thus cut costs – or, put simply, to increase their productivity. However, this rapidly accelerating digitalisation of workflows does not yet have that much to do with digital transformation.
What does “artificial intelligence” even mean?
That said, the use of AI is undoubtedly quickening the pace of this digitalisation and laying the foundations for genuine digital transformation. But what does this rocket fuel that is “artificial intelligence” mean, exactly? Because it is not that easy to pin down the very concept of “intelligence”, there are also several different ways of defining AI. One term that you often come across in this regard is (highly developed) “machine learning”. Here is an attempt to explain the possibilities that AI offers in layperson’s terms: Think of it as moving from simple “copy and paste” to “document understanding”, complete with conclusions, insights, and recommendations that get more and more accurate the longer an AI solution is in use. This is because, instead of having to be programmed using codes to handle every possible status as in the past, a “machine” now learns by recognising and combining patterns in vast amounts of data so that it can go on to make its own decisions. The dynamic way in which these analytical and decision-making processes evolve then opens up completely new potential applications.
AI in day-to-day life and industry
All of us are familiar with examples of AI thanks to the smartphones and tablets we use every day. AI navigates us through the huge volumes of data on the Internet, controls what product adverts and Netflix tips we see, filters out spam, enables voice control, and helps us to translate documents and websites written in another language. And its capacity for facial recognition keeps unauthorised users off our devices. Smart home devices, driver assistance systems, bank transactions – we can find basic AI or machine learning technologies wherever we look.
The twin drivers mentioned above – cost pressure and process speed – mean that business and industry are also already making widespread use of AI. For instance, it helps online retailers to understand their customers’ buying behaviour and generate tailored product recommendations for them. Meanwhile, other business applications use their algorithms to come up with ways in which companies can improve their business processes or, at the very least, individual features. This produces optimised leave, shift, and work schedules or a more accurate pricing matrix.
AI can also be used to support quality controls and quality assurance. Taking machine vision as a basis – a technology that has been firmly established for many years – software solutions for quality assurance can be combined with AI’s capacity for “deep learning”, significantly improving speed and accuracy while optimising costs.
Is AI good or bad news for workers?
This is a question that business owners, sociologists, psychologists, and many other groups of academics and practitioners are currently grappling with – and will continue to do so for some time yet. “Smart machines and robots reduce people’s workload by automating business processes and performing and monitoring them autonomously. Repetitive tasks and monotonous checks are minimised, labour is freed up for more important activities, and tactical and strategic issues can be focused on. Using AI enables people to turn their attention back to their core duties – creative problem-solving and social interaction.” Leslie P. Willcocks* is predicting that the use of AI and the end to mundane, highly repetitive tasks that it brings will significantly reduce the amount of work that needs to be done every day. This will increase employees’ job satisfaction and intellectual stimulation, allowing them to focus more on their most important responsibilities. Business owners and employers will also have more time to find ways in which, thanks to AI and the possibilities afforded by digitalisation, they can put their current business models through a genuine digital transformation or even develop completely new business lines or models. It’s time to get fit for the future step-by-step and stay that way.
*Leslie P. Willcocks is Professor of Work, Technology, and Globalisation and head of the Information Systems and Innovation Group at the London School of Economics.
Here is a list of products that already use AI:
