Today, ASEAN is the world’s fastest growing Internet market – it sees 125,000 new Internet users daily, and its digital economy is expected to add US$1 trillion to the region’s GDP over the next 10 years. According to a report by Google, Temasek Holdings and Bain & Company, the period of lockdown and isolation during the COVID-19 pandemic has seen ASEAN’s digital services grew as many as 40 million new Internet users, pushing the total number of users to 400 million in 2020 alone.
The race to provide richer and more responsive digital services that is very much data driven is on. ASEAN governments and businesses are already accelerating their digitalisation and shifting priorities to serve the growing demand for digital services. To name a few – In Malaysia, the government formed the Digital Free Trade Zone, where US$65 billion worth of goods are expected to flow through by 2025 and have previously set aside over US$239 million in the National Fiberisation and Connectivity Plan in 2019. In Thailand, the Digital Economy Promotion Agency was established to drive Thailand’s digital economy, where a budget of over $US41 million was allocated to digital transformation. Such policies and initiatives are a testament to ASEAN’s agenda to accelerate digitalisation moving forward.
Organisations must be prepared to tackle integration challenges and technology upgrades required both on the ground and in the cloud. They must process data and recognize processes in data accurately in a scalable fashion, where Artificial Intelligence (AI) is the solution.
The good news is that in a recent survey conducted by Juniper Networks, titled “AI is set to accelerate… Is your organization ready?”, majority of business leaders (95%) in Asia-Pacific are confident that their companies will benefit from AI technology in their daily operations, products and services, unlike their counterparts in North America and Europe. However, that being said, only 3% of ASEAN organisations have the right AI strategy and leaders in place to bring their vision to life.
Digitalising ASEAN begins from within and using AI can truly fast track ASEAN’s digitalisation journey. What can organisations do to leverage AI technology?
- CIOs and the vital role they play
It is paramount to ensure that a company’s CIO is well-equipped and well-versed to integrate AI, as he/she is the steward for all IT services in the organisation. These services, AI or not, must be secured and accessible to the business – the CIO will then be able to formulate a sound AI strategy and governance plan.
An AI strategy needs to be focused on how an organisation can use AI to solve unthinkable problems from the past. CIOs can go about this by 1) identifying which functions within the organisation are critical for the investment and building of user AI models 2) what kind of talent should operate AI – reskilling employees or hiring new talent 3) how to manage the AI data collected – set up a data supply chain and use it as a foundation for keeping stock on collected data.
An AI governance plan should be seen as an extension of the organisation’s data governance plan, where aspects such as communication and data security can be recycled. CIOs should also look to include additional AI algorithms and AI data models to ensure the accuracy of outputs – to maintain fairness and consistency in outcomes derived from an AI-driven decision. Most importantly, the CIO and his team must ensure that data collected is adequate to train AI models to avoid the obsolescence and outdatedness of AI algorithms and data models.
That said, CIOs should never be alone on this journey to adopting AI technology – companies must approach this as intentional as possible. Ideally, the CEO, alongside two or three top executives, must commit to drive AI technology in all business processes, where possible.
2. The best time to build/integrate AI
CIOs and top executives often ask “when is the best time to build AI” – the answer is right now. If a company is building AI from scratch, where there is a concern that data and/or models are too sensitive, a strong company background and AI team that is well-equipped with data science are required.
By outsourcing AI technology, companies will get to tap on leading industry experts who are highly skilled in this area. However, this could potentially come at the expense of training employees to have proper AI expertise, thereby limiting skills development overtime, as well as the lack of expansion for AI into other use cases.
On the flip slide, by building AI from the ground-up would boost AI know-how and capabilities internally, while having the flexibility to customize and integrate new processes and data that can help address the ever-evolving dynamics of the modern business. That said, this warrants a long-term commitment of resources and investment.
Ultimately, the build or buy decision is based on the type of AI initiative – whether it’s a one-off or long-term project. Organisations also need to make an informed assessment around existing resources, having employees with the right skillsets, processes involved and scale of data usage in order to operationalize AI for the business.
- Preparing talent to manage AI technology
Most enterprises want to embrace AI as part of their digital transformation strategy, but do not have the developers, AI experts and linguists to develop their own AI algorithms. Investing in employees internally in developing AI skills may be deemed as a long and tedious process but there are ways leaders and managers can go about ensuring that the process is a win-win for both organization and employee.
For starters, make it clear company-wide that there is a focus in developing AI technology moving forward and why that is important for the organisation and for employee growth. AI is often seen as a data-crunching job, but it is also perceived as an exciting and refreshing emerging technology for many people. Once that’s squared off, identify enthusiastic learners and offer them the opportunity to learn by having more AI-experienced employees lead workshops or classes.
Most importantly, introduce opportunities for learners to practice on AI-related projects – skills development is most effective when there is a hands-on approach to the learning. To further that, enterprises may even consider partnering with local universities to develop AI-related technologies with students, where the margin of error is larger than in real operations.
Lastly, executives and managers may start to look at launching pilot projects aimed at improving a process or solving an existing problem. These pilot projects may be derived from any department within the enterprise, including customer support, product sales or finance.
Integrating AI technology into the organisation may be daunting at first, but when adopted, integrated and sustained properly, AI will bring value and unlock the next stages of digitalization for your organization. In such times when governments are implementing policies and initiatives to drive digitalization within ASEAN, it will be prudent for enterprises to leverage on this to scale their businesses up with AI.
