By Christoforos Soutzis, CEO, Capital.com Europe
Every new technology arrives with a sense of promise, and risk. Artificial intelligence (AI) is no different. It can summarise, predict, and generate at incredible speed, but when organisations forget that speed is not the same as accuracy, things can go wrong fast.
In recent months, we’ve seen growing evidence across industries of what happens when automation runs ahead of accountability. AI-assisted reports, marketing materials, and even legal documents have surfaced containing made-up facts, non-existent citations, and confidently presented errors, all because someone trusted the output more than their own judgment.
These are not failures of technology; they’re failures of process. It's important to remember what AI is designed to do, which is to generate ‘plausible’ answers to a complex brief. The failure comes from people treating those outputs as finished products rather than starting points.
That distinction matters. AI is primarily a tool for acceleration, not accuracy. It drafts, summarises, predicts, and analyses , but it doesn’t understand. Without a layer of human validation, even the most sophisticated model can produce nonsense with absolute confidence.
What’s really at stake isn’t the reliability of AI, but rather our relationship with it. The danger of overconfidence cannot be overstated here. The assumption is that because a machine can write fluently, it must be right.
That’s why AI, when used responsibly, must operate inside strong guardrails. It needs a framework that combines transparency, review, and human accountability at every stage. Otherwise, speed becomes a liability rather than an advantage.
Supported by the right culture, AI is an enabler
Across industries, AI is already transforming how people work. Used well, it saves time, enhances creativity, and frees up energy for deeper thinking.
At Capital.com, AI isn’t confined to the research or engineering teams, it’s woven into daily life. Every employee, regardless of department or seniority, has access to leading AI tools. From ChatGPT and Google Gemini for ideation , co-writing and analysis, to GitHub Copilot and Cursor AI for coding and debugging, these tools have genuinely transformed how we work.
They’ve shortened the distance between idea and execution, allowing teams to focus on creativity, problem-solving, and experimentation instead of repetitive tasks. Projects move faster, collaboration feels smoother, and everyday conversations are backed by smarter data and better insights. AI hasn’t replaced the human element , it’s amplified it, helping everyone at Capital.com think bigger and move quicker without losing the human touch that defines our work.
Our adoption of AI is deliberate and culturally driven. Innovation isn’t controlled from the top down, it’s democratised. By giving every team member access to cutting-edge AI tools, we enable experimentation at scale and empower people to reimagine how they work.
Marketers use generative AI to test campaigns in real time. Engineers rely on AI models to speed up code reviews and automate system testing. Legal and compliance teams use it to summarise complex regulations and spot potential risks early. AI has become part of how we think, learn, and collaborate. Everyone is encouraged to use it, question it, and find smarter ways to solve problems.
Innovation through AI is now a measurable part of performance. Every employee is encouraged to ask: How can AI help me work smarter today?
Guardrails matter
But there’s a difference between using AI and leaning on it. The key lies in culture and process. Every AI output at Capital.com passes through human review. Teams are trained to verify sources, test assumptions, and document where AI was used. The technology is there to assist, but the final call always rests with a human being.
That’s the point many organisations miss. The true power of AI isn’t in replacing human intelligence; it’s in augmenting it. The question isn’t “Should we use AI?” but “Do we have the right guardrails to use it responsibly?”
Those guardrails start with culture. Organisations need to make human oversight non-negotiable. Every piece of AI-generated work should be checked by a qualified person who understands the context. Transparency is essential too. If AI contributed to a report, clients and stakeholders should know. Hiding its involvement creates risk while openness builds trust.
Traceability matters just as much. Teams should keep records of prompts, data inputs, and human edits, especially in high-stakes or regulated environments. When something goes wrong, there should be a clear chain of responsibility.
And finally, none of this works without training. Giving people access to AI isn’t enough; they need to know how to challenge it. They need to be comfortable spotting bias, verifying facts, and knowing when to push back.
When those principles are embedded in culture, AI becomes a creative partner, not a compliance risk. It drives innovation without losing integrity and accelerates progress without cutting corners. It's important to remember that AI can write, but it can’t reason. It can analyse, but it can’t empathise. It can inform, but it can’t be accountable.
Those are still very human jobs. And when people stay firmly in that loop; curious, vigilant, and responsible; AI doesn’t replace them. It amplifies them.