AI Adoption in workplaces will accelerate in 2021

Andy Watson, senior vice president and general manager for Asia Pacific Japan and Greater China at SAP Concur, predicts that automation will become essential, and that the pace of digital change in business and society will increase sharply

As businesses maintain hybrid remote-working models and anticipate other potential disruptions in 2021 and beyond, the role of automation and AI use cases in the workplace will grow

Digital transformation has been the talk of the town for the longest time, but it is only during times of necessity that we see an acceleration of digital transformation in many organisations.

The pandemic in 2020 has seen many companies in the early and mid-stages of digital transformation adapt and speed up their transformation to address the unprecedented global disruption.

As businesses maintain hybrid remote-working models and anticipate other potential disruptions moving forward, the role of automation and AI use cases in the workplace will grow

Moving into 2021, as businesses maintain their hybrid remote working environment and anticipate other potential disruptions, artificial intelligence (AI) and machine learning (ML) will play a greater role than ever.

What’s more exciting is that due to rapid adoption of technologies like cloud, AI and data analytics, the Asia Pacific digital transformation market is projected to grow at a CAGR of 20.7 per cent from now to 2025. This makes APAC the world’s fastest-growing region (global CAGR is 16.5 per cent).

Automation will therefore start to be an essential part of APAC organisations’ work processes in many aspects.

1. Improving workflow efficiency
The broader use of AI and ML allows businesses to eliminate manual processes, improve productivity, and get a competitive boost. An SAP Concur survey conducted earlier in 2020, for instance, has shown that as many as 38 per cent of employees are still processing claims manually in the Asia Pacific region.

The emergence of the digital business environment is expected to increase pressure on companies to manage budgets in real-time, increase compliance and eliminate errors.

The adoption of AI and ML also opens up new possibilities for travel and expense management. Prompt reimbursement, and reduced manual review and approval of claims, are some possibilities that finance teams in organisations can expect from AI and ML adoption.

Algorithms can be trained to pick up fraudulent claims, which can be missed by human beings. Automation allows mundane tasks to be eliminated from employees’ workflow, and finance teams can spend more time looking at expense reports that contain privacy violations and fraudulent expenses.

At SAP Concur, we use AI and ML to make everything from travel booking to expense auditing smarter, more automated, and easier for employees.

2. Adding intelligence to applications
AI and ML are not only useful in eliminating manual processes. Adopting automation into an organisation’s workflow can bring extra value to employees at a different level to grow, scale and improve employee satisfaction.

By introducing AI and ML to an organisation’s workflow, employees can receive recommendations for business travel and accommodation options based on their history, and yet still be compliant with company policies. ML algorithms can be used to analyse employees’ behaviours and recurring patterns for the system to provide the most suitable options. When the algorithms are properly trained, the perfect travel options can be provided with just the first few recommendations.

AI and ML are not limited to travel options, and automation can play a role in intelligently adjusting travel policies within organisations’ expense management systems based on the data mined. Employees booking flight tickets or accommodation at prices that exceed allowed limits would typically be flagged for violation, but the AI-analysed data can allow the system to automatically adjust travel policies to accommodate current prices so that employees would not be flagged for violation. This way, other departments will not have to intervene and slow down processes.

3. Empowering business leaders’ decision making
At a higher level, AI and ML can sieve through a huge amount of data and garner key insights from it, swiftly empowering business leaders to make important business decisions.

Finance managers are always on the lookout to cut travel-related costs, and often need to gather insights on which business processes are prone to cash leakages. With automation being the key driver in gathering and analysing data, key insights and recommendations can be delivered to business leaders to action on, while providing an overview of organisations’ travel and expenses domain such as employee behaviour, travel expenses, spending and travel patterns.

AI and ML can deliver decision making value at an even higher level when the system is tasked to deliver risk assessments on the next key business decision while considering all historical projects. Business leaders can then make informed decisions based on comprehensive insights rather than perspectives to maximise budget management and liquidity, increasing compliance and eliminating errors, and maximising profitability.

As we head into 2021, there’s no doubt that the clear business value AI and ML bring will increasingly see them being integrated into organisations.

Andy Watson is the senior vice president and general manager for Asia Pacific Japan and Greater China at SAP Concur, where he is responsible for leading the business for SAP Concur in this region. A 30-year IT industry veteran who’s been a CFO, Watson has also held global and regional leadership roles in SAP SuccessFactors and SAP Cloud.

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