Edmas Neo

刻舟求剑: Rethinking AI Transformation in a Changing World

Mon, 17 Aug 2026 22:06:08 -0700

刻舟求剑

(kè zhōu qiú jiàn)

AI may be new, but many organisations are still using old assumptions, workflows and operating models. 刻舟求剑 offers a surprisingly relevant lesson for transformation leaders today.

I learnt about this Chinese idiom when I was a kid and even memorised it for Chinese composition examinations. However, I cannot remember using this phrasein my daily conversations ever since then. Recently, I came across this phrase again and as I reflected on its meaning, it really got me thinking about the wisdom behind this phrase and how relevant it is in this fast-changing world today.

刻舟求剑 (kè zhōu qiú jiàn) describe s a man whose sword fell into the water while traveling on a boat. He then made a mark on the side of the boat where the sword fell hoping to retrieve the sword later from that spot. We laughed at his ignorance as the boat with the mark had already moved on while the sword remained where it fell in the water.

As I reflected more deeply, this story is about how one may still rigidly follow old assumptions while being oblivious to changing circumstances or use old solutions to solve evolving problems and hope to get the same results.

I am not saying that the lesson of 刻舟求剑 is that old knowledge has no value. Rather, it is that a reference point is only useful while the conditions that made it valid remain unchanged.

This further got me...Read More

Governing Goal-Oriented Agents

Thu, 23 Jul 2026 01:36:05 -0700

Governing Goal-Oriented Agents

At a recent forum, I spoke about the importance ofgovernance and guardrails in deploying goal-oriented agents, and the need to have clear guidelines. This is especially crucial when it comes to resource prioritisation and agent orchestration.

In a hyper-accelerated organisation, hybrid departments may deploy their own agents to achieve departmental goals. Situations will inevitably arise where there are conflicts and contention when accessing organisational resources to achieve individual goals. These resources will need to be prioritised and allocated.

For humans, we can set up meetings to negotiate the use of such resources. However, this will be very different for departmental agents.

In the recent case involving OpenAI, and in a few other examples, goal-oriented agents appear to be fixated on achieving their goals and may try all means to achieve them.

Often, when it comes to AI governance, organisations tend tofocus on external-facing controls and guardrails. There may be a lack of similar considerations and guidelines between departments. This will inevitably create weaknesses in controls and increase the risks of AI deployment.

As such, a robust AI governance structure...Read More

The IDEAS 2.0 Co-Innovation Maturity Model

Wed, 08 Jul 2026 08:23:29 -0700

Over the last decade, I have observed a changing pattern in how corporates approach innovation.

There was a period when many organisations moved quickly into visible innovation activity. They launched innovation labs, organised hackathons, hosted technology showcases, sponsored accelerator programmes, partnered with ecosystem platforms and visited innovation hubs around the world.

These activities created energy. They helped corporates connect with startups, research institutions, technology companies, design studios, solution providers and ecosystem partners. They also helped organisations signal that they were serious about innovation.

However, in more recent years, there has been a noticeable shift.

Some corporates have pulled back from activity-led innovation. Others have become more selective, asking harder questions about business value, adoption, productivity, cost efficiency, customer impact, revenue opportunities and measurable outcomes.

This shift is important.

Innovation should not be measured only by the number of events organised, ideas collected, pilots launched or partners engaged. These activities may create momentum, but they do not automatically create value.

The more meaningful question is whether innovation helps the organisation become more competitive, productive and cost-efficient, while creating new revenue opportunities, improving customer outcomes, strengthening sustainability and becoming more future-ready.

Why Co-Innovation Is Harder Than It Looks

On the surface, collaboration between corporates and external innovation partners should be a natural match.

Corporates have problems, customers, assets, industry depth, operating environments and scale. Innovation Solution Providers, or ISPs, bring speed, specialised capabilities, emerging technologies, fresh perspectives and the...Read More

Hyper-Accelerated Startups: AI-Native Venture Platforms Redefining Startup Creation

Sun, 07 Jun 2026 09:02:14 -0700

Hyper-Accelerated Startups: AI-Native Venture Platforms Redefining Startup Creation

he Presentation

Through the story of John, the Founder, and Tim, the Venture Builder, this presentation explores the challenges they face in building and scaling startups. It looks at how different ecosystem models have evolved over time to support founders and venture builders, and how the arrival of AI and AI agents is creating new possibilities for hyper-acceleration. The presentation also examines how this model could work in practice for both startups and venture builders.

View on SlideShare.com

Article

Read the article on Hyper-acceleration here.

Discussions & Comments

For discussion and comments on this topic, pRead More

Artificial Workforce Interruptions:

Fri, 05 Jun 2026 08:59:36 -0700

by Edmas Neo

Today, I asked a question during an AI forum on Business Continuity Planning in the age of AI. The response I received was that AI should be treated like any other IT system. If the AI is unavailable, the BCP approach should be no different from any other application outage.

To any risk manager, that should be an alarm bell. Not because the answer is necessarily wrong, but because it may suggest that people are still viewing AI as a tool rather than understanding how AI is changing workflows. The risk of this blind spot is real.

Traditionally, most enterprise systems are tools used by people. If an ERP system goes down, people can still perform parts of the work manually. If a workflow system becomes unavailable, staff can still use emails, spreadsheets, phone calls, and paper-based processes. The organisation slows down, but it continues to function because the people, knowledge, and capabilities are still there.

Agentic AI is different. Increasingly, organisations are no longer using AI simply as a productivity tool. They are redesigning workflows around AI agents. The AI agent is no longer just helping with the work. The AI agent is becoming part of the workforce. As organisations move towards AI-augmented or AI-first processes, agents may eventually take over 20%, 30%, or even more of a workflow. At that point, an outage is no longer just a technology outage. It becomes a workforce...Read More

Lean Before AI: Why Workflow Still Comes First

Wed, 03 Jun 2026 08:01:15 -0700

Lean Before AI: Why Workflow Still Comes First

AI has moved from chat, to being embedded into tools, to helping people improve personal productivity.

But for AI to deliver real organisational value, we need to go beyond individual productivity. We need to look at the workflow itself.

Recently, I have been hearing more about the term Forward Deployed Engineer. The idea is that engineers are attached closer to user teams. They spend time understanding the workflow, learning the domain, identifying the pain points, and then designing AI workflows that can actually work in operations.

In my view, this is the right step forward.

While the AI industry calls them Forward Deployed Engineers, the underlying principle is familiar to many transformation teams.

Spend time with the business. Understand the workflow. Identify the pain points. Then redesign the workflow and the solution.

This is why I think the work of transformation teams is becoming even more relevant.

Over the past few years, I have led a team of transformation managers who worked closely with business units on Lean transformation, DILO studies and workflow optimisation. We spend time with business teams to understand how work is actually done, identify bottlenecks and pain points, and improve the process.

Through this approach, the transformatoin team has helped identify improvement opportunities and supported smoother service delivery with less frustration for staff and guests.

This is also why I think organisations should start thinking about Lean Before AI.

Before applying AI, understand the workflow. Optimise the process. Reduce wasted cycle time. Remove unnecessary steps. Then apply AI where it can create the most impact.

In some cases, organisations may also need to design AI-first workflows in parallel, instead of only improving the current process.

For Transformation...Read More

Part 2: Hyper-Acceleration - The Next Operating Model for Startups

Tue, 14 Apr 2026 21:00:15 -0700

Figure 2: AI created illustration based on the article

If incubation, acceleration, and venture building were each responses to the problems of their time, then Hyper-Acceleration is the response to the new AI era. In my view, this is not just an incremental improvement. It is a more fundamental shift in how startups may be designed, operated, and scaled from day one.

Instead, to scale a startup, we are no longer just talking about the number of headcounts. In an AI-native startup, I expect a 30:70 ratio to become increasingly common, though not necessarily as a rigid formula for every company or industry. In many cases, only 30 percent of the team may need to be human, focused on strategy, decision-making, innovation, relationships and governance, while 70 percent consists of AI agents executing functions.

The tight integration of Hybrid Human-AI processes, together with AI-first operational workflows across a large part of the startup’s functions, could allow startups to scale much faster. It may also create more consistency in workflows as the startup expands across different countries while maintaining central oversight. That said, market nuances still matter. Regulation, customer behaviour, language, and local business culture will continue to require human judgement and local adaptation. In general, the HQ will have a much easier task in maintaining central oversight or initiating changes.

From Incubation to Venture Building: How Startup Creation Evolved

Tue, 14 Apr 2026 21:00:06 -0700

From Incubation to Venture Building: How Startup Creation Evolved

Startup growth and development is a topic that is close to my heart, and which I have been involved with for a number of years. When designing and running programmes like Infocomm Investment’s TAGPASS, ACE’s BACECAMP, and Accrete’s SEA Anchor, I always take a practical and realistic approach. Having seen the methodology shift firsthand, I can say with certainty that the way we built companies a decade ago is now obsolete.

We have moved through incubation, acceleration, and venture building. Each phase emerged for a reason. Each responded to a limitation in the previous model. Looking back, the evolution is actually quite clear, and it also explains why the next phase of startup creation is now beginning to take shape.

Roughly Pre-2012: Incubation, Technology First

When I look back at the earlier days of incubation, the focus was almost entirely on technology. Most work happened in research labs where the goal was to commercialise a specific invention. As a mentor, our role was to provide space and funding, but we rarely looked at the customer.

This naturally led to many "solutions" looking for a "problem." While developing the technology was the hardest part then, the clear drawback was a total lack of speed to market. We were building in a vacuum.

Most organisations do not lack ideas. Many even have access to promising technologies and startups. Yet despite innovation programmes, pilot projects, and corporate labs, very few innovations actually scale into real operations.

Over time, I have noticed that the reason could be quite simple. Innovation is often treated as a project, when in reality it is an ecosystem effort and this should be an integral part of the organisational strategy.

When I talk about ecosystem, I do not only mean external partnerships. I also mean the internal ecosystem within the organisation. Innovation is rarely the responsibility of a single department. It requires multiple stakeholders playing different roles, moving in a coordinated and symbiotic manner to drive change.

Innovation and ecosystem building have always been two things very close to my heart. Through my work across startup ecosystems, accelerators, and corporate innovation initiatives, I have had the opportunity to observe how organisations attempt to innovate and where many of these efforts succeed or struggle.

One pattern appears repeatedly. Organisations launch innovation programmes, run pilots with startups, and set up labs or sandboxes. Yet very few innovations actually scale into real operations.

Through...Read More

Part 2: Time Zones of Innovation

Mon, 08 Dec 2025 20:00:45 -0800

Just as people across different time zones work together seamlessly and the world keeps spinning, organisations also rely on different internal time zones to move forward. When these zones are aligned, the organisation keeps pace with change. When they are not, everything slows without anyone noticing until it is too late.

Following Part 1 of my article Surfing the Innovation Wave, here is Part 2 on Time Zones of Innovation.

Part 2: Time Zones of Innovation. Why Misalignment Kills Transformation.

In Part 1, I discussed about when to innovate, and how organisations can use the Gartner Hype Cycle as a guide to ride the tech wave. But timing alone does not guarantee success. Even with the best roadmap, innovation can still stall or die quietly inside organisations. One of the biggest reasons can be attributed to internal misalignment, more specifically, different groups of people within the organisation working in different “time zones,” and having different priorities that pull the teams in different directions, often with the right intentions but different lenses. In many ways, this...Read More