Tajinder Virk, Co-Founder and CEO, Finvasia Group and Dealing, discusses the rise of artificial intelligence, its growing use across real-world applications, and why AI-focused companies are drawing investor attention.
Artificial intelligence is rapidly becoming a defining force across the global economy, influencing everything from enterprise automation and cloud computing to financial services and healthcare. As adoption grows, investor interest is also rising, particularly around companies building the infrastructure, software, and applications powering this transformation.
Tajinder Virk, Co-Founder and CEO, Finvasia Group and Dealing, spoke to Tahawultech.com and shared his views on AI’s rise, where it is creating tangible value, and why investors are closely watching the sector.
Interview Excerpts
Artificial intelligence is dominating global technology conversations. What is driving this surge in interest?
AI has been talked about for years, but it’s no longer the future. It’s very much the present. What started as discussions has now moved into real adoption, with organisations across sectors actively experimenting and using it in their work. It’s also no longer limited to tech companies or specialists. AI has become accessible and easy to use, where people can build workflows or even simple apps within minutes using different tools.
And the impact is already visible: teams are working faster, processes are becoming more efficient, and organisations are starting to see real value from it. It’s also helping organisations execute today what they earlier saw as long-term ideas.
How would you describe the current stage of AI adoption globally?
Generative AI adoption is growing rapidly, with new tools coming in almost every day. What’s really driving this is how easy these tools are to use; they’re helping people speed up research, work, and everyday processes. At an organisational level, AI is no longer just in the experimentation phase. It’s getting embedded across functions from operations to customer experience to decision-making. There’s also an early shift towards more execution driven systems, including agentic AI, where workflows can be managed with minimal manual intervention.
“What matters now is not access to AI, but how effectively organisations can integrate it into everyday decision-making and execution by keeping customer requirements at the centre. ”
Where are some of the most visible real-world applications of AI today?
AI is already being used across industries in very practical ways. In finance, it helps with risk checks, fraud detection, and quick decision-making. In healthcare, it supports diagnostics and patient monitoring. In logistics, it makes forecasting and routing more efficient. And in enterprise tools, it’s helping automate work and improve productivity. What’s interesting is that AI is no longer limited to any one industry, but it is something that businesses across sectors have started to use in their own way. At the same time, companies are working towards driving the impact of AI on the bottom line through cost efficiency, improved processes, and faster decision-making. It is no longer just a corridor discussion, but it is a boardroom discussion where AI adoption plans are made, roles are created, and impact is measured.
How do you see AI reshaping investment platforms and wealth management in the next few years?
AI is already becoming a natural part of how investment platforms are evolving. At the same time, personalisation is no longer a good-to-have—it’s something investors now expect. As attention spans shrink, people are naturally drawn to platforms that understand their needs, behaviour, and goals, instead of offering the same experience to everyone.
In many ways, AI is not just changing the platform experience, but also how investors think and make decisions. By 2027, AI-driven tools are expected to become a primary source of advice for retail investors, with usage projected to reach around 80% by 2028, according to Deloitte. You can already see early signs of this shift—better engagement, higher adoption, and more informed decision-making.
But the real impact goes beyond automation. It’s about helping investors make better sense of information—giving them sharper insights, better portfolio guidance, more efficient decisions, and, importantly, building discipline over time.
“Platforms like Dealing.com are part of this broader shift towards more intuitive, intelligence-led investing experiences, as the market increasingly moves towards scaled, capability-driven businesses.”
Will AI reduce the gap between retail and institutional investors, and how will it change the way investment decisions are made?
AI can help narrow the gap by giving retail investors better access to research, portfolio insights, and decision-support tools that were once largely available to institutions. It will make investing more data-led, accessible, and personalised, even though institutions will still retain an advantage in scale, execution, and proprietary intelligence. This is where platforms such as Dealing.com reflect a wider market direction, helping make market intelligence and investment tools more accessible to a broader investor base.
What are the biggest opportunities and risks AI creates for the financial sector going forward?
The biggest opportunity is that AI is no longer just an automation tool. It is becoming agentic, which means it can analyse information, make recommendations, and handle large parts of financial workflows with limited human intervention. Across wealth management, research, compliance support, and portfolio monitoring, AI could take over much of the heavy lifting, while human professionals focus more on oversight, judgment, and regulatory guardrails. The risk is that finance still depends on trust, explainability, and compliance. Anything shaped by regulation or external market structures will continue to need human supervision.
“The real challenge will be knowing where AI can act independently and where human control must remain central.”
How do you see AI impacting trading behaviour—will it reduce noise or increase it? How do you see the future of investing with AI?
AI will likely do both. It can reduce noise by filtering weak signals, improving analysis, and removing some of the emotion from investment decisions. At the same time, it could increase market noise if too many participants rely on similar models and react in the same way. The future of investing is likely to become more agent-led than application-led. Traditional interfaces may become less important as investors increasingly rely on intelligent systems that understand goals, act on intent, and support execution. In that model, the human role will shift from doing every task manually to setting objectives, defining guardrails, and supervising outcomes.
