Damian Leach
Workday’s Chief Technology Officer, APJ
Despite tough economic conditions, geopolitical conflicts, supply chain disruptions and the continuation of the pandemic, 2022 was the year of digital transformation. Business leaders brought forward digital investments previously earmarked for a post-pandemic era in order to drive their organisations towards more sustainable profitability. At a time when digitisation has become integral to the way organisations operate, technology continues to be a strong enabler for businesses to build
resilience, gain agility, and thrive amid uncertain environmental macro conditions. Here are some of our predictions for the top business and technology trends in 2023.
1. Retaining, developing, and reskilling top tech talent to maintain competitiveness and revenue
Specialised technology professionals will remain in high demand, as businesses across all sectors continue to develop their digital capabilities, deliver new technologies, and drive digital agility. According to a report by recruitment and solutions company, GRIT, starting salaries in the technology sector are the highest in Singapore. The gap between availability of local talent and demand in technology roles makes Singapore even more attractive as the hub of Asia in which to live and work.
In 2023, we will see IT leaders increasing their efforts to attract, retain, grow, and upskill talent. In addition, there will be a rise in traditional internship programmes as focus shifts to building the talent pipeline. Forward thinking organisations will build relationships with established education facilities. This will be key for the more mature technology companies, as they seek to attract the brightest minds.
Today’s technology workforce must be flexible, willing to learn new skills, and proficient in emerging technologies to help businesses innovate, adapt faster, and better navigate uncertainty.
We also expect more companies to tap into newer, Artificial Intelligence (AI) driven optimisation solutions whilst leveraging machine learning models, enabling IT leaders to adopt a skills-based people strategy to better support their team members’ career and skills development needs. This will encourage both internal mobility and building skills for existing tenured employees, whilst moving them from manual activities to more interesting and higher value strategic work.
2. Reducing technology experimentation and shifting focus to building scale, adaptability, and resilience in unison with elevating the employee experience
In 2023, technology will play a greater role in driving and elevating the employee experience. We expect hybrid work arrangements to continue and this is supported by an IDC report stating that more than 56% of employees in Asia Pacific want flexible work even beyond the pandemic. As economic borders reopen, and business operations rise to pre-pandemic levels, we expect to see a large increase in local and overseas ‘gigs’ or short-term assignments for workers, as organisations adapt to retain talent and elevate the employee experience.
As organisations start to bed down, scale, and focus on key investments made during the pandemic to enable collaboration across their workforce, we foresee a reduction in experimentation as organisations bed down the right tools for their business. This involves consolidating and reducing the tools that were experimented with during the pandemic. Decisions are being made to integrate collaboration tools with core systems, so employees have a unified and omnichannel experience.
This shift will see strategic investments that strengthen a cloud-first approach to technology; building on the emerging cloud backbone, tight integration and open APIs that provide everyone the same experience, no matter the user’s location or device.
Organisations will strive to create an integrated cloud experience; CIOs will be implementing measures to understand the utilisation of applications, tools, and services with the aim of reducing complexity and increasing resilience. The CIOs’ aim to enable a frictionless experience for employees whilst keeping data secure and meeting increasing regulatory needs will remain a delicate balance.
In addition, we will see a focus from CIOs and line of business (LOB) to strategically reduce organisational silos that had previously created ‘technology islands’ within their organisations. This came to a head during the pandemic as it led to additional operational and security risks, especially for legacy applications that couldn’t integrate, had security gaps, limited support, and often installed on legacy fixed premise infrastructure.
As such, legacy systems will continue to be decommissioned as organisations recognise they must modernise to the cloud to stay competitive. Delaying the decision to do so is far more costly in the long run.
3. Push for the use of ethical Artificial Intelligence (AI) technology models alongside Machine Learning (ML) to drive growth and accelerate the employee experience
AI is becoming increasingly prevalent across our daily lives, and a new generation of ethical AI technology and refreshed modelling is emerging. The benefits and use cases of AI to complement ML for large amounts of data are growing. The unification of ML and ethical AI is enabling organisations to gain greater efficiency and create actionable insights that help guide the business forward in true terms.
The use of ML in finance digital transformation enables finance professionals to automate accounting, reporting, and financial planning and analysis (FP&A) processes, thus enabling greater efficiency and agility. Besides numbers, in modern organisations AI and ML is also used to understand employee sentiment by automating action pertaining to employee wellbeing, growth, development, and ultimately cultural happiness in an organisation. Listening with intent and creating insights from the data are key to happy employees and in turn, great organisations.
With AI growing in prominence, there are growing concerns about how businesses and employers will use AI and ML technology. As a result, there will be emergence of ethical AI that removes model bias. For this emerging technology to take off in the coming years, companies must provide greater transparency on how their AI is applied.
The compliance and open book analysis of how AI and ML is being applied will allow organisations to establish greater trust, thus allowing the advancement of enterprise AI adoption on a wider scale. More providers will begin disclosing how their ML models lead to their outputs (e.g., recommendations) and predictions, possibly even at an individual level.