The Intel · Celia Rizothanasi · 6 min read
In December 2025, we sat down with my co-founder Agis and our guest Sotiris Karagiannis, Chief Innovation Officer at Space Hellas Group, AI pioneer and early AI entrepreneur who was among the very first to study artificial intelligence at the University of Edinburgh, to talk about the strategic direction of AI.
Not the hype. Not the shiny tools. The big picture.
What followed was a wide-ranging conversation about where AI is genuinely heading, what is holding businesses back, and where the real opportunities lie. Here is what we unpacked.
AI is becoming an operating system, not just a tool
We have gone from chatbots to agentic systems that browse the web, analyse documents, trigger workflows, and even transact on our behalf. The direction of travel is clear: AI is quietly becoming an operating system sitting between people, data and business processes.
For business leaders, especially in the mid-market, this raises uncomfortable questions. Where is the technology going in the next couple of years? What will change in how we build products, serve customers and organise work? And what happens to the companies still on the sidelines while their competitors are deploying these systems?
The internet analogy, but accelerated
Sotiris drew a sharp parallel between the early internet and today’s AI landscape.
It is amazing how I see the analogy between the early internet days and today’s AI. There was a hype, but everybody was trying to understand what the internet would provide. Now we know — it took us a lot of years to understand the full value of the internet. AI is something like this, but with a huge difference in terms of acceleration.
The lesson: just as businesses that moved early on the internet captured lasting advantage, the same is happening now with AI. The difference is that the window is narrower. The acceleration is real.
Voice will be the next big shift
One of the most striking takeaways was Sotiris’s conviction about voice AI. Not as a gimmick, but as the primary interface through which people, and then businesses, will interact with AI.
I think that voice will go faster, and in one or two years, we all will be talking to some kind of our own AI assistant, not only for our work, but also for doing things in our everyday lives.
The implications go deeper than convenience. These fast voice interactions will need to be supported by huge systems behind them — data systems, backends, cloud services, even local edge compute, and on-premise computing for companies that do not want to share proprietary information.
Agis reinforced the point from personal experience: even today, the voice models are not that good. But when he is driving, he can call the voice agent and have a discussion — research, projects, working through a problem out loud.
The shift from typing to talking is not trivial. It changes how we interact with machines, and it lowers the barrier for people who might otherwise resist AI adoption.
Why businesses are not getting ROI yet
Companies are enthusiastic about AI, but the results are not materialising. Sotiris was blunt about why.
Companies have not understood yet how they can do that, and there are not enough people to actually consult them. So they are making very small steps. Usually they just want to jump onto the bandwagon of AI. They are doing it in the wrong way, and they get disappointed.
He pointed to a noisy market where everybody says they are an AI expert, without the depth of experience to guide a business through implementation. His advice was clear: find a reliable person to consult you, then take small steps. Define your early wins. Find the lowest-hanging fruit. Build from there.
Agis added a reality check many businesses need to hear. After almost ten years in this space, he still meets companies who are sure they have good data. Before looking at it, he can usually tell them they do not — because they never collected the data with a use in mind.
The 1:10 cost ratio that should keep leaders awake
Based on what I am seeing already, the ratio of the costs — the cost of the previous process to the cost of the new one — is about one to ten. So if you do not automate fast enough, you are going to operate at ten times more cost than your competition.
That is not a theoretical risk. It is already happening in areas with simple, repetitive work that can be automated, from report generation to media assets to routine processes. The businesses that move first do not just save money. They change their cost base.
Two types of opportunity: productivity and innovation
We identified two broad categories of AI opportunity for businesses.
Productivity. Doing what you already do, cheaper, faster and better. Sotiris urged companies to examine which processes they can make faster and cheaper as a starting point.
Innovation. Doing things you could not do before. From AI-powered research at scale to agents that actively discover new customers, the possibilities are genuinely new.
Imagine that you can leave your agents to go out and find your new customers. You could not do that with the internet. You had a good page, they had to come to you with SEO. But now agents can discover your new customers out there.
The future of search, and commerce, is AI-native
Sotiris flagged something that should be on every business leader’s radar: the future of search itself is changing.
We will be searching through AI. A lot of things, including e-commerce, will change. Also the way you present your company will change, because the information is going to be gathered from the AI. So you will want to optimise the way AI processes this information. This alone is like a huge industry.
If customers find you through AI agents rather than Google, your entire digital presence strategy needs rethinking.
Are we overreacting on regulation?
The conversation turned to data governance. Sotiris posed a provocative question: people throw personal data into every kind of social media, then say they do not want that data used. In his view, European regulation is decelerating things.
Agis drew an analogy with agricultural rules: very rigid standards for our own produce, while imports arrive with none. Do the same with technology, he argued, and we will simply import innovation — and the data — that someone else built.
Their shared view: regulation has a role, but fear is a poor strategy. The real risk is not in using data. It is in standing still while competitors do not.
The public sector and safer cities
Agis shared a use of AI that sits outside the usual commercial frame. The public sector holds information about taxes, revenues, companies and health. He is interested in fixing cities and making them safer with data that can be collected without personal information — anonymous, open and closed data that can still make a city safer, starting with women’s safety.
Small and global: the new shape of business?
Can small teams with fully integrated AI agents operate globally from anywhere? The answer was nuanced.
On the services side, there is an amazing possibility. You can produce knowledge or services that can work with 25 customers, delivering your services without you being awake.
Then the reality check: if you are producing a physical product and you do not have the logistics, smart agents will not deliver the goods. Digital services, yes. Supply chains, no.
The bottom line
AI is moving from a tool you use to an operating system you work within. Voice interfaces will accelerate adoption. The businesses that start small, get their data strategy right, and find reliable guidance will pull ahead — and the cost gap between movers and waiters is already widening.
As Sotiris put it: time is of the essence. Businesses do not need to do everything at once. But they do need to start.
Sotiris Karagiannis is Chief Innovation Officer at Space Hellas Group, an AI pioneer and early AI entrepreneur. He studied artificial intelligence at the University of Edinburgh.
This article is based on a two-part live conversation recorded in December 2025 between Sotiris Karagiannis, Celia Rizothanasi (co-founder and AI Strategist, Intelligent Acceleration) and Agis Georgiou (co-founder and AI and Data Science expert, Intelligent Acceleration).