SCMAP Perspective is our fortnightly column on PortCalls, tackling the latest developments in the supply chain industry, as well as updates from within SCMAP. On this column, Henrik Batallones looks at what recent developments in the artificial intelligence space tells us about the roadblocks and challenges businesses face in digitalization.
Some more thoughts on digitalization
A few weeks back, the world of technology – and specifically the world of artificial intelligence – was upended by the unveiling of the first large language model (LLM) from Chinese company DeepSeek. It was purportedly developed at a much lower cost than other existing LLMs such as OpenAI’s o1 and Meta’s LLaMA, and with much less computing power, too. This, despite the arms race that developed around the sector in recent months, with the United States government going as far as banning the export of its most advanced chips to China for fear of their rival surging ahead.
There’s one thing that this development stresses – and I’m not thinking of the geopolitical implications. Despite the massive levels of investments by major tech companies, DeepSeek has demonstrated that it is possible to develop such technologies with less. Cue pleasantries about how ingenuity will see a company, or a country, through. Again, I’m not thinking of the geopolitical implications. Rather, look at it this way: if you fear that fully embracing the possibilities offered by technology to your business is expensive, then you definitely have to think again. You don’t require the most advanced of resources – and perhaps an abundance of it – to embrace a technology.
Considering how many years it has been since the pandemic made most businesses realize that “digitalization” is not just a buzzword or a competitive advantage but a necessity, there are still some enterprises – particularly smaller ones – who are hesitant to get started. Perhaps part of the apprehension lies in the belief that going digital must mean going big on the first go. I know we in the logistics sector can sneer at the idea of some still relying completely on Excel spreadsheets for inventory management, but micro-enterprises can boost their productivity – and possibly their service levels and profits – if they embrace Excel rather than a handwritten log.
In fact, a business’ initial exposure to technology can lead to it being more open to further digitalization in the long run – of course, at the pace of its growth, rather than going big when it isn’t necessary. Key here, as always, is the role of partners – not just solution providers, but also business support groups and the government – in assisting these businesses, making the case, and easing the transition.
The other challenge is to make sure that our workforce is truly digital-ready – not just adept with current tools, but ready to embrace future ones as well. Sure, the Philippines may be the social media capital of the world, boasting of deep penetration of mobile devices, but that does not mean all of us are adept to utilizing, more so maximizing, technology. The question stems back to the basics: if we are able to comprehend what we read, figure out logical sequences and can discern based on evidence rather than just on preconceptions and assumptions. Addressing these issues goes back to whether our education system – from the very beginning – is able to foster this. It’s not my expertise as this is a column about supply chain, but a ready workforce does not begin in college.
Back to artificial intelligence: the DeepSeek news also presents businesses, especially those with the resources, many questions. Suddenly one does not need to fully rely on external suppliers to utilize AI – perhaps one can build their own in-house models for use within their operations only? A wild, expensive thought, but one worth pondering on, too. After all, while we all talk about generative AI and what lies beyond it – artificial general intelligence – we have already been dealing with AI in many ways in our own business, from analytics to chatbots. Latest developments could serve to democratize these tools further and evolve the role our workforce is playing – although in the case of AI, these come with increased demand for electricity and water, and perhaps an increased carbon footprint, too.
But again, it all boils down to one question: we may be able to get over our apprehensions and step in, or go deeper, into our use of technology in our businesses, but are our people up to the task? Can we upskill them quickly enough? And more importantly, is the path we’re taking truly the right one for our business?