When it comes to business decisions, speed and accuracy both matter. But in today’s fast-moving markets, most companies still rely on outdated information to chart their course. That’s a problem Ian Philips has spent over two decades solving. As GM of Full Stack Observability at HCLSoftware and a veteran of technology innovation, Ian brings a fresh perspective on how AI can transform boardroom decision-making without losing the human element.
Getting Real-Time Insights That Matter
Business moves fast. Monthly reports? They’re already outdated by the time they hit the boardroom table. That’s where AI-driven business observability comes in. “Board decisions should be based on real-time insights, not static reports,” Ian explains. He’s seen too many companies trying to steer by looking in the rearview mirror. The solution? Bringing everything together where leaders can see it. “Bring large amounts of data together in a real-time view to make the right decisions to move your business needle forward, rather than wait for a month-end report,” Ian says. It’s not just about having more data – it’s about seeing it clearly, right when you need it.
Managing Risk and Compliance Smarter
Talk to any business leader today, and you’ll hear the same concerns: risk management and staying compliant. Ian’s take? “In today’s fast-changing technical landscape, risk and regulatory compliance is everywhere—and real-time decision making is paramount to be compliant and to stay ahead of the competition.” But here’s where it gets interesting. AI isn’t just crunching numbers faster – it’s changing how companies handle compliance entirely. “AI-powered solutions reduce the time and demand for compliance officers to evaluate, aggregate data to prove to regulators they comply with laws and regulations,” Ian points out. His team’s GenAI solutions go even further, breaking down regulatory documents and matching them with the right data to show compliance.
Some tech leaders want to automate everything. Not Ian. “I am a firm believer that we should not take the human out of the loop as expertise,” he states. Instead, he sees AI as a way to scale human expertise. Think of it like having your best people’s knowledge working 24/7, without burning them out. This approach shows up in how his team uses digital twins – AI models that can provide a second opinion on repetitive decisions like fraud analytics. It’s not about replacing human judgment, but supporting it around the clock.
Building Trust Through Data Transparency
In the world of AI, trust isn’t given – it’s earned. Ian emphasizes that, tracking data’s journey isn’t just about checking boxes. “Traceability and data lineage are paramount in proving regulatory compliance,” he explains. “Without a clear chain of evidence, showing where the data originated, how it was transformed and who accessed it, organizations cannot demonstrate their adherence to regulatory compliance.” This kind of transparency does more than satisfy regulators. It builds trust with everyone involved – from employees to customers to shareholders. Every step of the data’s journey needs to be clear and accountable.
The future of business decision-making is already here. AI-driven insights aren’t just nice to have – they’re becoming essential for staying competitive. But Ian’s final thought cuts to the heart of what makes AI truly valuable in business: “Numbers tell you what happened; business context tells you why it matters. By understanding the context in real time, you can make the right decisions faster.” That’s what it all comes down to – not just faster decisions, but better ones. AI might crunch the numbers, but it’s the combination of machine intelligence and human wisdom that really moves businesses forward. As Ian sees it, that’s where the real competitive advantage lies.
For boardroom stakeholders and decision-makers looking to stay ahead, the message is clear: real-time insights, powered by AI but guided by human expertise, are the key to navigating today’s business challenges. It’s not about replacing human judgment – it’s about giving it the support it needs to work at scale. To connect with Ian Philips and learn more about his insights on AI-driven business observability, visit his LinkedIn profile.
