Artificial intelligence is being adopted by organisations across the world to make better decisions, to innovate and to achieve increased efficiency with intelligent automation of business processes. This is leading organisations towards what I call ‘enterprise autonomy’ – and to a world in which the majority of what we today call office work is automated.
‘I define autonomous enterprises as having the bulk of their transactional and simple decision-making processes automated.’ (Photo by Chaay_Tee / iStock)
In my book ‘The Autonomous Enterprise – Powered by AI’, published by BCS, The Chartered Institute for IT, this week, I define autonomous enterprises as having the bulk of their transactional and simple decision-making processes automated, but that is not all. They also tap the enormous amount of data that they are capturing from their digital and automated transactions for analysis and decision support. They use the data extensively to optimise their processes and business operations and, importantly, to innovate.
Analyst forecasts point to accelerating autonomy in the enterprise. In its ‘Worldwide Artificial Intelligence Spending Guide’, IDC forecasts that global spending on AI systems will jump from $85.3bn in 2021 to more than $204bn in 2025, a compound annual growth rate (CAGR) of 24.5%. Everest Group predicts that market for intelligent process automation software and service will reach $10bn this year, a CAGR of 40% to 50% from 2020.
Other reports reveal the drivers for this adoption. The market research company, Forrester, for example, has published a series of total economic impact assessments of enterprise deployments of intelligent automation software with reported returns on investment upwards of 100%. Everest Group has shown evidence of advanced adopters of intelligent automation achieving more than a 60% reduction in the cost of running some processes, adding capacity of between 100 and 500 full-time equivalent (FTE) employees, and 100% reduction in process errors thanks to their adoption of intelligent solutions.
With results such as these, it is unsurprising that organisations are turning to intelligent process automation. As knowledge work is incrementally automated, alongside growing investment in digital channels and other technology capabilities, it is easy to see how we will reach a stage when the bulk of transactional and basic decision-making in enterprises will run autonomously. In fact, there are examples of such companies already, including US-based insurance company Lemonade and other fintechs.
Efficiency has been a business priority since the dawn of commerce, and on its own is enough of a driver for organisations to transform into autonomous enterprises. Another is the ability of AI to support decision making. Organisations are increasingly getting their analytic insights in real time.
Furthermore, through analysis, AI can help generate new ideas for innovation, enhance many types of product and services, and enable disruptive new business models. As set out in my book, autonomous enterprises will make extensive use of AI’s analytic powers to make good decisions and to innovate. New companies are also often disruptors and I believe there are huge opportunities for more disruption with AI, to bring new products or services to market using novel models.
There is also a place within the innovation cycle for creativity. Experimental research in art, writing and abstract reasoning show how AI can enhance the human capacity to look at the world in a different way and, in doing so, open up new possibilities.
Where will enterprise autonomy take us?
We must consider where these developments are taking us and understand the nature of the change that is already happening, the opportunities that we are gaining and the risks we are facing.
Given the direction of travel towards autonomous enterprises, it is essential today that we get the ethics of AI, and technology as a whole, right.
Importantly, given the direction of travel towards autonomous enterprises, it is essential today that we get the ethics of AI, and technology as a whole, right. This means developing guidelines, best practice and even regulations for the development and application of them. The sooner governments and the industry take definitive action the better.
It is logical to think that enterprise autonomy will lead to mass unemployment for humans. I believe that will not happen because autonomous enterprises will still employ people with a mix of technical and non-technical skills, to deploy, supervise and maintain the automations, to handle more complex requirements, to design, build and expand the range of offerings, and to run and grow the business.
That said, I do believe that the way that we work, and our organisational models will change. This is one reason why embedding ethics into every step of the transition to enterprise autonomy is essential.
It’s such an exciting time in technology, and I hope my book will help organisations see the bigger picture as they navigate their way towards enterprise autonomy. Governments need to understand the path we are on too, so that they can support their industries and build a strong skill base for the future.
