But about 75 per cent of companies not ready for AI: Workday
Artificial intelligence will help staff make faster, better decisions, not replace them in the workplace, says AI and machine learning (ML) experts at Workday.
“Our philosophy on AI and machine learning is value-based; that is, we still value human interaction,” says their Asia Pacific Japan chief technology officer Damian Leach. “We are using AI and ML to solve real business problems and to help companies adapt faster.
“AI enables repetitive work to be automated but, importantly, we are not taking humans out of the equation; we still ensure that a human makes the decision. We call this keeping the human in the loop.
“Through AI and ML, we can free up time for them to make more complex and strategic decisions. Organisations themselves can also make more intelligent decisions through greater insight from huge amounts of data.”
Global software-as-a-service firm Workday recently commissioned a survey “AI IQ: Insights on Artificial Intelligence in the Enterprise” involving 1000 HR, finance and IT decision-makers around the world, including 150 in New Zealand and Australia.
The survey found 93 per cent of business leaders believe it is important for a human to assist AI or ML when making significant decisions, rather than allowing the technologies to do it alone.
Nearly three-quarters of the respondents (73 per cent) are under pressure to increase adoption or investment in AI and ML. For IT leaders, it’s the pressure to support overall business competition; for human resources people, it’s improving the employee experience; and for finance it’s addressing the skills gaps.
From the survey, 77 per cent of the respondents are concerned that their organisation’s data is neither timely nor reliable enough to use with AI and ML; 72 per cent felt their organisation lacks the skills to fully implement the technologies; yet 81 per cent said they need AI and ML to be competitive.
Leach says successful adoption of the technology requires a commitment to keeping humans in the decision-making loop and working with partners committed to responsible AI to maintain data integrity.
Workday, which specialises in cloud applications for finance and human resources, has been integrating ML into its software platform for the last 10 years.
“We are playing a leading role in leveraging AI and shaping how it will influence the future of work,” says Leach. “We have become a trusted source of truth for people and finance. We believe AI will further unlock human potential, drive business value and allow customers and their employees to focus on higher value, more fulfilling work.”
Established in 2005, Workday has 10,000 customers with Fletcher Building, Mercury Energy, Southern Cross Medical Care Society, Barfoot & Thompson amongst its 70 in New Zealand. Workday is hosting a customer event on August 8. Its Auckland office, opened in 2015 and employing nearly 200 people, is the biggest in Asia Pacific, Japan and Workday in New Zealand has expanded to Wellington.
A developer team is based there, because of the availability of local talent, to support the development and launch of payroll for Australia. The Auckland operations also include the award-winning Security Operations Centre, one of three with Pleasanton (Californian headquarters) and Dublin (Ireland), working seamlessly to ‘follow the sun’ and provide 24/7 global security monitoring, detection and response capability for Workday’s services.
Over the past 18 years, Workday has built an impressive set of human resources and finance data stored in the cloud on a single code line and single secure multi-tenanted data model.
Workday has more than 60 million employees under management which represents over 400 billion transactions a year. “Whilst that’s a lot of Data, because we made a conscious decision to design our ML to be embedded in our core, we can operate this at scale using a federated learning model as such we are already delivering business value to our customers” says Leach. “The ML is accurate and trusted because of the type of data we are managing for customers, that is people and finance.
“The way that we have designed our architecture from the ground up means we are able to continually innovate. There is only one version of Workday – which keeps us incredibly focused.”
Workday has developed over 40 use cases or applications involving AI and ML. One of them is workplace skills. Using its ML technology, Workday identified 12m skills across Accenture’s 700,000+ strong workforce and was able to categorise up to 20 skills for each employee. This allowed Accenture to move to a skills-based workforce, match talent to roles, create gigs, set career paths for employees and direct learning and development plans accurately across the globe.
“It’s important for both an organisation and its employees to understand the skills they have on hand and the skills they need to develop for a career pathway – this is a perfect job for ML and leveraging cloud-based platforms and this can scale and perform and consider multiple dimensions way beyond that of legacy on premise systems or manual processes” Leach says.
“It allowed Accenture to move to a skills-based approach for its entire workforce, so whenever a gig or three to six-month project came up, Accenture could advertise it internally rather than searching for people outside.”
Workday has developed AI for the management of expenses, using optical character recognition. Employees working out of the office can take a photo of their expenses on their mobile phone. The photo is converted into text and uploaded to their own expense personal account with the currency, taxation and type (of expense) taken care of.
“During this process, a person reviews the expense before applying it – despite AI and ML being used in this process, we still value and believe that humans need to be in the loop with critical interactions,” he says.
He says it’s a “super exciting” time for Workday. “We will always be innovating for our 10,000 customers (Workday spends US$1.5 billion a year on innovation). We need to make sure our ML and AI is built on high-quality data and establish clear use cases and strategy with our customers, such as helping organisations overcome skills gaps.
“We are transparent and can explain our ML & AI models from an ethical point of view. We build and launch two major releases, featuring new capabilities, features and enhancements to code, to solve real business use cases every single year.
“These updates, enhancements and features are applied to all our 10,000 customers at once globally there is no need to forklift any platform to accommodate it customers can turn the new features on themselves. We believe our customers should be empowered to adapt and leverage the latest features as soon as we release them.”
Join Workday at Discover Auckland on 08 August, 2023