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 CEO'S PERSPECTIVE 

Pieter Verkade
CEO | Digicel T&T

LINKAGE Q2 (2026) - IMPACT
Every Big Change Always Seems Impossible at First
A lot of talk about AI and data centres is happening across Trinidad and Tobago right now, and if you listen closely, it has a familiar sound. We hear phrases like: "This will not work here." "Could we get it to scale for impact?" "The economics do not add up." The talk is loud, it is confident, and of course, there are a lot of experts. But the reality is: almost every major shift in how people live and do business was met with the exact same certainty of inability, right up until it stopped being true.
In early days of GSM (what you know as 2G), when I worked in Norway back in 1998, we were explaining the business case for new Mobile Operator Licenses. At that time, the market view, and specifically the view of the banks, was that mobile would never go beyond 40% penetration. Today, it's hard for people to imagine life without their mobile.
Fear of change is loudest right before change happens, not after. It is usually the last sound a threshold makes before it gets crossed.
It's the same fear we hear when we talk to leaders about the first steps of AI adoption: transforming their data models and investing in cybersecurity. There is always skepticism about whether it will really work, trepidation about cost, or an absolute certainty about security (until there is a breach, of course).
The Process Excellence Network (PEX) Report 2025/26, a global survey of enterprise leaders, found that just over half of organisations name poor data quality as the single biggest barrier to AI adoption, ahead of cost and talent.
So yes, AI will be a major economic transformation. But the real amplification comes if successful AI adoption is achieved. The first step is high-quality clean data. And what use is that data, however good it becomes, if it is not protected? In a society where data still runs on spreadsheets and cybersecurity is dealt with only after the fact, that is the gap we risk building into our own foundation. AI will take time to arrive in the mass market. We can start curating quality data, and protecting it, today.
​The Data Problem Nobody Wants to Admit
Walk into many boardrooms in this country and decisions are still made the way they were made twenty years ago. On instinct. On what the CEO's gut says. Data exists, but it sits in spreadsheets nobody trusts, in systems that do not talk to each other, in reports generated because someone asked, not because someone is using them.
The businesses afraid of this shift are not wrong that it feels like a large undertaking. Where they are wrong is in thinking it stays optional. The business that learns to harness data properly will eventually take the customer, the market share, and the advantage away from the business that keeps guessing. There is a warning most companies skip too. If you feed a system bad data, you get bad answers, and bad answers delivered quickly and confidently are more dangerous than no answer at all. Clean, reliable data has to be the starting point, because everything downstream depends on it.
The good news is that this does not require solving everything on day one. The instinct in most organisations is to automate every process at once, and that instinct is exactly what makes the fear feel justified. The better approach is to start with the one problem customers actually have most often, solve that first, learn from it, then expand. That is how large transformations actually happen, not as one leap, but as a series of solved problems that add up, in hindsight, to something that looks inevitable.
For example, we have made an intentional decision at Digicel to use data and automation in further improving our customer experience. This includes practical fixes, like automatic alerts when a truck has taken down a fibre cable, something that still happens too often, as well as longer-term work, like training our AI-based customer experience tool. For the latter, this is our goal: make sure the data we feed it is clear and specific to our market, so customer queries can be resolved in one call.
​Is Security Really a Luxury? 
The second fear is cybersecurity. For a long time it has been treated like insurance, something people are very passionate about after something happens, and a line item that gets deferred until calamity strikes.  
In T&T and the wider Caribbean, some expenditures are luxuries until it becomes an emergency, and the price we are willing to pay for protection tends to rise only once a threat feels credible. But that is backwards. The value of what you are protecting should set the price of protection, not the fear of a threat that has already arrived. If your data is becoming the engine of your business, protecting it has to be treated with the same seriousness as the opportunity itself. They are the cost of playing in this new AI-driven environment because now there are rogue AI agents breaking out of sandboxes and hacking businesses by mistake. Could you imagine if cyber-criminals become more targeted with this kind of power and intelligence at their disposal? 
The truth is this: cybersecurity is a bit like insurance. It increases your costs without any clear benefit until something happens. As AI puts greater onus on the quality of our data, it also becomes obvious that we need to protect this data, with cybersecurity and with geographical backups, for example at different locations like data centres or in the cloud.
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Getting Ahead of the Inevitable
None of this is theoretical. It is already playing out in how businesses here compete for customers, and it will only accelerate as AI infrastructure becomes part of the national conversation. The question was never really whether AI data centres can work in Trinidad and Tobago. The louder that argument gets, the closer we probably are to the moment it stops being an argument.
The businesses that spend this moment building clean and secure data foundations will not be scrambling to catch up when that moment arrives. The future is here, embrace its possibilities and stay positive.