Nguyen Thuong Tuong Minh, CEO of Base.vn: “AI has the ability to plan strategies and provide feedback like a CSO”

As someone managing a platform used by thousands of businesses, when did you most clearly feel: Are we simply repeating the same mistakes in our organisations—only now with newer technology?

Technology has certainly given us tremendous support, yet the most crucial factor remains management thinking. Changing the mindset is always the first step we take with any business. Every organisation needs a group of pioneers willing to lead transformation, those who not only understand but embody and are committed to implementing the new principles of system-based governance.

That said, not every enterprise is able to adapt at that level. We’ve seen many corporate governance projects fail, with companies having to endure considerable difficulty before eventually reaching meaningful success.

Last year, we released an internal publication, Behind The Success, a compilation of hard-earned lessons from common failures. The book also outlines key implementation approaches designed to help businesses improve the success rate of their technology projects.

We are fascinated by the breakthroughs of AI, but I believe that once the initial excitement fades, we will need to seriously reassess the role of human thinking in this era, because it ultimately shapes how we use technology and where we find its true value.

Have you ever felt like you were not just building software, but slowly changing the way people in your business think, work, and make decisions? Where do those moments usually come from: a piece of feedback, a piece of data, a moment of silence?

Perhaps I’d rather share a story in place of a direct answer. Last year, Base joined a project to implement a management system at a hydroelectric plant tucked deep in the forests near the Vietnam/Laos border. We were there to train the plant’s engineers and workers on how to use the software. The sessions were held during their break at 10 pm, but still, they sat attentively, learning to operate Base’s platform on their mobile phones.

The following day, as operations resumed, the atmosphere had shifted. Digitalisation had begun to transform the daily routines of the plant’s engineers, mechanics, and workers. Approval processes that once took an hour were now completed in just 15 to 30 minutes, significantly reducing operational loss for the plant.

What we are most proud of isn’t just that Base has reached such remote corners, but that it is genuinely helping businesses navigate their operational challenges and grow.

At Base, I always remind my team that each statement, each line of code we write, is more than an algorithm, it’s a story that holds meaning and brings value to the businesses we support.

You just mentioned that digital tools can silently restructure organisational behaviour. So when AI comes along, with its ability to learn, predict, and make recommendations, how will digital management solutions themselves change? Are they still ‘tools’, or have they become ‘decision ecosystems’?

AI has moved beyond the stage of merely synthesising and extracting information. It can now analyse data across multiple dimensions. More crucially, it doesn’t just offer projections and suggestions for us to consider; it can learn independently, offering analyses tailored to specific sectors, regions, services, or manufacturing industries. Many AI tools today already outperform human capabilities in collecting and processing data, often uncovering insights in places we may never have thought to look. In that sense, I believe AI will soon have a direct hand in many of our decisions.

If current digital governance systems still rely heavily on static processes and predefined data input, how will AI change that structure? In what ways will it blur the lines between data, action, and decision?

I believe AI is transforming two core aspects of business management, what I temporarily call “pair” and “peer”. Not long ago, AI functioned mainly as a support mechanism, working alongside humans. Now, however, we are seeing AIs with the capacity to act more independently, especially when integrated with systems like HRM, WorkFlow, and CRM. At Base, for instance, our content department has already automated 80 per cent of its workload with AI. Rather than spending time on repetitive tasks, our team now focuses on creativity and quality assessment of AI-generated output. Even routine responsibilities such as responding to enquiries about employee welfare policies can now be efficiently handled by AI. As it transitions from a “supporter” to something closer to a “colleague”, the line between human and machine becomes less and less distinct.

It can be said that AI is transforming digital solutions into entities that are increasingly “self-learning” and “self-operating”. So, in this AI-driven era, are we looking at digital systems that make decisions, or architectures that continuously learn?

I believe it is both. AI is becoming a decision-making system built upon a foundation of continuous learning. Every activity in a business, be it a rejected approval, a delayed task, or the loss of a customer, is living data. AI does more than record these events; it interprets them, draws insights, and reintegrates that learning back into the system.

What we’re building is akin to a distributed nervous system that senses, adapts to mistakes, and becomes more accurate over time. It no longer simply manages the business; it evolves with it.

In the future, CEOs may “converse” with AI as they would with a CSO (Chief Strategy Officer) when making strategic decisions. At that point, will digital management solutions serve as mirrors reflecting the organisation, or will they become participants in the strategic process?

In fact, this isn’t the future. We’ve already begun. I’ve experimented with positioning AI as a real CSO. It can absolutely assist in strategic planning, but perhaps more intriguingly, it offers counterarguments. And some of these are remarkably creative—ideas we would never have reached, despite all our time, effort, and investment. Naturally, as AI’s ability to challenge ideas improves, a pressing question emerges for both of us: what skills must managers develop to avoid being “outpaced” by these systems? Personally, I believe our role will be to ask better questions.

Do you think digital management products in the next five years will evolve into organisational ecosystems where every action, feeling, and data point is instantly recognised and addressed? What stands in the way?

I don’t believe we need to wait five years. I wouldn’t call this a warning, but businesses must adapt now. The emergence of AI at every level of organisation, management, and operation marks a shift quite distinct from the digital transformation wave we welcomed not long ago. Without pioneers in this space, many businesses will inevitably fall behind. But the real barrier remains the mindset we’ve already discussed, an outdated way of thinking that holds companies back from embracing digital management products.

These AI-powered tools are not merely what we see in headlines or glossy demos. They have a direct impact on fundamental outcomes such as reducing operational costs or enhancing competitive advantage.

Even so, mindset alone isn’t enough. The next hurdle is implementation. Where should a business begin applying AI? What level of investment suits its scale or sector? This is the practical challenge we’ve seen repeatedly when supporting businesses, particularly small and medium-sized ones. And it’s why we are committed to working closely with them, helping to shift perspectives and introduce digital management in the most practical and effective way.

Many businesses assume that deploying AI requires vast data sets and an expert team. So what are the three essential conditions for an SME to adopt AI effectively?

This is a broad question, and difficult to answer fully. Still, I would like to offer three suggestions for SMEs.

First, cultivate a systems mindset towards AI. Leaders must take the initiative to understand AI and begin to see it as an integral part of their operational strategy.

Second, frame the problem correctly and select the right tool, not by chasing technology, but by identifying actual operational needs and choosing solutions that genuinely add value to the business.

Third, find the right partner. Rather than doing everything in-house, businesses should focus on long-term, sustainable solutions through collaboration with developers and AI service providers.

As someone building a platform for thousands of businesses, which management concepts have you found yourself re-evaluating? KPIs, performance reviews, accountability, leadership—are these still relevant?

I don’t believe the theory behind these management principles will change significantly. What is shifting, however, is the operational engine; how it works on the ground. The presence of AI is reshaping how information flows, enabling us to transmit and absorb data at all levels and stages, while bridging gaps in traditional hierarchical and decentralised data structures.

Elements such as KPIs, performance metrics, responsibility and leadership remain fundamental pillars of management. If management theory is a car, then AI is the new engine powering it. But with this change, these familiar metrics are no longer measured in fixed ways. AI engines are like turbines, constantly in motion, accelerating outcomes in ways traditional approaches cannot. At Base, our own software design is continually evolving to suit each business’s specific character. In doing so, we create a more precise and meaningful management system optimised for each enterprise, thanks to the participation of AI.

In a world where AI supports decision-making at every level, from executives to team members, what new skills must administrators develop to avoid being “left behind” by their own systems?

It’s a wide-ranging question, as there are many tiers of leadership. But broadly speaking, business owners at the highest level need to regularly assess performance outcomes in the context of AI integration. They must develop a clear understanding of the real value that AI contributes to their business.

At the next level, managers need to assemble a capable team of people who can interpret and carry forward AI-driven strategies across departments. At the most fundamental level, managers must foster a workplace culture where AI is not only accepted, but embraced. At Base, when we first introduced AI, many employees felt hesitant, assuming it had little relevance to their roles. Today, that mindset has shifted. Our teams now take initiative, think creatively, and suggest AI-driven solutions. In this way, AI has not replaced people; it has helped them evolve into more empowered, more capable versions of themselves.

Article published from the original in Tatler Vietnam, June 2025 issue

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