Author: Nicky Metcalfe-Dennis
In this blog we discuss how automation and machine learning look set to revolutionise the workplace of the future.
The nature of work is changing rapidly. One of the key drivers of this change is the increasing use of automation and machine learning.
These technologies are already having a major impact on the way we work - and we can expect them to become even more prominent across our workplaces in the years to come.
In fact, research by US online jobsite Zippia found 73% of business leaders believe machine learning will double the productivity of their employees.
But will embracing new tech be a benefit or hindrance to businesses?
Here, DocTech's managing director Ruban Rajasooriyar gives his predictions on how it is likely to shape the office of the future - and the potential benefits and challenges these changes could bring.
One of the biggest benefits of automation and machine learning is the ability to automate routine and repetitive tasks, such as data entry and processing.
According to Deloitte’s 2018 Global Human Capital Trends report, 47% of manufacturers are already supporting their current workforce using automation, with 24% using artificial intelligence (AI) and robotics to perform routine tasks, while 16% use automation to augment human skills.
As more of these mundane tasks are automated, staff will be able to focus on more complex and creative work.
As such, we are likely to see increased job satisfaction and engagement as employees spend more time on more engaging tasks that require creativity and problem-solving.
The WorkMarket 2020 In(sight) Report by KRC Research, found 85% of business leaders believe workload automation will give them and their employees more time to focus on the goals which truly matter to the company.
This constantly evolving tech can also help to improve efficiency and productivity in the workplace.
Organisations have been quick to improve physical inefficiencies but the admin processes such as document approvals are often still heavily reliant on manual input from staff.
According to KRC Research, 52% of business leaders believe they could automate 10-30% of their daily workload.
When a task is repetitive, the person doing it, again and again, can get complacent. Automation can prevent or at least minimise human error. Repetitive tasks are often easy to automate making workstreams more accurate and efficient.
In fact, according to Forbes, AI implementations can help boost productivity by 54%.
In January, Manchester housing group Mosscare St Vincent’s, for example, revealed it saved £22,500 per year by migrating its paper-based maintenance reporting processes – just one part of its overall operation - online.
Machine learning algorithms can also be used to analyse large datasets and identify patterns and trends that might not be immediately apparent to human analysts, enabling firms to make better decisions based on data-driven insights.
Another potential benefit of automation and machine learning is the ability to provide more personalised experiences for customers and employees.
Machine learning algorithms, for example, can be used to analyse customer behaviour and preferences, and make personalised product recommendations based on that data.
This will inevitably lead to improved customer satisfaction and loyalty.
According to Earthweb, 48% of businesses are using machine learning to effectively make use of large data sets.
Reducing Labour Expenses
As automated processes increase, it is likely that organisations going through high growth won’t need to constantly recruit, meaning labour costs will be less draining on profits.
A report by PWC suggests up to 30% of existing UK jobs could be impacted by automation by the early 2030s, yet it also highlights “new AI-related technologies will also boost productivity and generate additional jobs elsewhere in the economy".
A shifting job market could create a need for workers to reskill in order to stay competitive in their industry.
DocTech customers, for example, are now able to migrate 85% of manual admin and data input tasks to automated digital solutions, saving them vast amounts of time and money.
As these technologies are given more autonomy and control, businesses must remain transparent and accountable in their use of automation and machine learning.
Developing ethical guidelines and implementing oversight mechanisms to ensure fair and responsible use will be vital.
It may also involve investing in training and reskilling programs to help workers adapt to the changing job market.
What is almost guaranteed is automation and machine learning will play a pivotal role in office of the future.
