The events of the past two years have shown how organisations across every sector were forced to digitally transform their business models overnight. Banks had to create web portals to manage an influx of loan requests. Meanwhile, meal delivery services had to leverage automation and self-service to support customers when they needed it.
In fact, a recent study by Singapore Business Federation revealed how the COVID-19 pandemic drove 42% of Singapore companies to increase their investments in new technologies and digitalisation efforts in 2022, compared to 2021.
As organisations continue to emerge from a significant reset in how employees engage and operate, the future of work has become an integral component of overall digital transformation strategies.
The future of work is underpinned by data
While it’s known that data-driven organisations are more successful, the reality is many companies are not driven by data, and their employees are not able to access or engage with the data they need to make informed decisions.
We know that one of the biggest challenges to data democratisation is data literacy, or the ability to read, work with, and understand data. Take the frontline warehouse operators of healthcare services provider Zuellig Pharma, for example. They are non-IT specialists who are trained to harness the power of data and analytics to inform supply chain decisions. They are also empowered to review real-time operational KPIs and dashboard-driven statistics to understand how processes impact their KPIs.
So, as the future of work continues to evolve, it’s time to recognise that low- to no-code AI is now at the front and centre of this evolution. It’s no longer just nice to have; it’s a necessity. But why?
Enter: No-code technology for skills development
Gartner predicted that the low-code technology market will reach US$29 billion by 2025 with a compound annual growth rate of over 20%, showing the extent of the opportunity here.
We’re also seeing how shifts that have taken place in the labour market are becoming more pronounced, with many people voluntarily quitting roles just as the demand for workers rises and economies reopen.
No-code AI can break down barriers and alleviate resource constraints by putting data in the hands of business users. For instance, an account executive on the sales team can tap low-code or no-code data science capabilities, or what we call Business Science, to explore various possibilities and see which scenarios will best help their customers achieve their goals.
At a time when budgets have to stretch further, natural language and augmented analytics can help businesses drive meaningful decisions, removing the current burden placed on IT teams. Just as clickable icons have replaced complex programming commands, new no-code technologies replace programming languages with intuitive interfaces. For instance, AI-powered data stories can add automated plain-language explanations to dashboards to help businesses understand and interact with data, at speed.
Bottomline: This means more people across different lines of business are better equipped to tackle tough questions like resource allocation, prioritisation, staffing, and logistics, among others – all without being a data scientist.
The demand for data skills is only growing, and with it, tremendous opportunity to help people and organisations learn and solve problems more effectively. Making low- to no-code tools accessible will directly empower employees and build a resilient workforce.