For more than a decade AI has been changing our lives, barely noticed as it worked away in the background, unlocking our smartphones with face recognition, monitoring our banking transactions for suspicious behaviour and guiding our cars to avoid traffic.

Then came ChatGPT. Suddenly, AI was the centre of public attention – and finding its way on to the agendas of executives and boards.

Workday, a leading enterprise platform that helps organisations manage their most important assets – their people and money – has been exploring, developing and using AI for more than 10 years.

“We’ve now reached the stage where business leaders believe that AI can benefit their business, but many aren’t sure where to start,” says Esther Monks CA, Asia Pacific and Japan industry advisor at Workday.

A Workday commissioned report – Insights on Artificial Intelligence in the Enterprise – found that 80% of decision makers consider AI a must if they are to remain competitive. However, 75% see obstacles to implementing AI and its subset machine learning (ML) effectively. Many also have reservations around data quality and privacy.

“The report found that businesses of all sizes are facing three main challenges – being able to trust the quality of the data they use, establishing clear use cases to adopt AI and overcoming the skills gap,” says Monks.

Quality data

AI algorithms use training data to learn and grow. This can be generated by the organisation itself – customer information, for example – or accessed via third parties like Workday.

“Some business leaders are yet to understand how much data is required to teach algorithms,” says Monks. “They also want to know how they can be sure that data sourced both inside and outside the organisation is high quality and that the algorithms are built in an ethical way.”

This is made harder by the fact that AI is yet to be regulated.

“Many governments around the world are working to introduce regulation, but it’s a complex challenge as they try to stay ahead of AI development,” she says.

Clear use case

The research also suggests that some decision makers are concerned about how AI will coexist with human talent.

“It’s important for both employers and employees to understand that AI has the potential to augment what their people do, rather than replace them,” says Monks. “Including employees in the initial discussion around the tasks that AI can automate and how they actually benefit from this is a great way to start building trust and, ultimately, improve the application of use cases.”

Once in place, it’s vital that the technology is fully integrated, easily accessible and feels like a natural extension of an employee’s regular job.

“You can only gain full value from AI if the recommendations are front and centre for people when they are making decisions,” she says.

Overcoming the skills gap

AI can help shape a future workforce, even when skills are in short supply.

“In the finance sector we’re seeing a reduction in student numbers, coupled with a loss of skills due to an ageing profession approaching retirement,” says Monks. “By automating lower-value, routine tasks, AI and ML can enable organisations to upskill their workforce and build a pipeline of talent.

“As an accountant myself, I’ve seen how much time can be consumed by closing the books, analysing results and preparing for the following month end,” she adds. “The more we allow and enable technology to assist us in those processes, the more time we can spend supporting our organisations on the productive, value-creating work we really enjoy.”

Read the full AI report

To find out more about how smart technologies can transform your business, download Workday’s AI IQ: Insights on Artificial Intelligence in the Enterprise report.