Techie Tonic: Monday morning gap - Why CIOs and CISOs are struggling to turn cyber data into business decisions

Every Monday morning, in boardrooms across the globe, a familiar tension is quietly building. Faced with an overwhelming volume of cybersecurity data and a constant stream of emerging threats, senior leaders are being asked a deceptively simple question: what truly matters right now?

For Chief Information Officers (CIOs) and Chief Information Security Officers (CISOs), the challenge is no longer about visibility. Years of investment have ensured organisations can detect risks with remarkable precision. The real struggle lies elsewhere; that’s in translating complex technical signals into clear, actionable business decisions that executives can understand, trust, and act upon with confidence.

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We had an interesting conversation with two prominent CISOs, namely Ankit Sastangi and Chenthil Kumar. A- Head of Information Security, Red Sea International to understand their views on this.

“We’re not short of data,” Ankit said during a recent discussion on enterprise cyber risk. If anything, we have too much. Threat feeds, vulnerability scans, compliance trackers, and it’s endless. But none of it answers the one question the board asks every week “what should we do?”

Across industries, organizations have invested heavily in detection technologies over the past two decades. Security Information and Event Management (SIEM) platforms, threat intelligence systems, compliance frameworks, and monitoring tools generate vast streams of information every second. Yet many executives say the flood of data has created a new problem “decision paralysis”.

“That’s exactly the challenge,” a Chenthil explained. “Finding threats isn’t the hard part anymore. Explaining them is.”

According to the executive, technical teams often understand the details of cyber risks, but translating those risks into language that resonates with senior leadership remains difficult.

“Try explaining risk to a CFO who wants financial exposure quantified, or to an audit committee looking for assurance in plain terms,” added Ankit. “Then the CEO reads about a competitor suffering a major breach and asks, ‘Could that happen to us?’ That’s where everything breaks down.”

The question whether organizations were overinvesting in tools while still struggling to answer basic business questions.

The response was immediate.

“We’ve spent years building detection capabilities,” added Chenthil. “But there’s a missing step between signal and decision.”

That missing step, both executives agreed, is interpretation, converting technical findings into measurable business impact and actionable recommendations.

At present, much of that work remains manual.

“It depends on a small number of highly skilled individuals who can speak both languages, that’s both security and business,” Chenthil noted. “They take raw technical data and convert it into something meaningful for leadership. But if those people are overwhelmed or unavailable, the process stalls.” So, we need a solution, like a storyteller where no human emotions involved.

The result, Ankit added further, is that board members often receive either overly technical dashboards they cannot interpret or simplified slide presentations that fail to drive action.

The growing use of artificial intelligence inside enterprises is making the challenge even more urgent.

“Employees are using AI tools in ways organizations never designed controls to handle,” Chenthil warned. “Sensitive information, like customer records, financial data, strategic documents is being uploaded and processed outside traditional corporate boundaries.”

The phenomenon, increasingly referred to as “Shadow AI,” is rapidly emerging as one of the biggest blind spots in enterprise security.

“And we can’t see it effectively,” Ankit admitted. “It bypasses traditional data loss prevention systems and often sits outside existing regulatory frameworks. It’s happening at scale, across almost every organization, mostly under the radar.”

Both executives argued that the industry’s next major breakthrough will not come from another detection platform or dashboard. Instead, they believe organizations need systems capable of consolidating external threats, internal vulnerabilities, compliance obligations, and AI-related exposure into a real-time understanding of enterprise risk.

More importantly, they said, those systems must provide prioritized recommendations rather than endless alerts.

“The board doesn’t want severity scores or technical jargon,” Ankit said. “They want to understand the financial and operational impact in business terms and know what action to take before Monday morning begins.”

Despite billions spent globally on cybersecurity technologies, both leaders acknowledged that this gap between intelligence and action remains unresolved.

“The most expensive unsolved problem in enterprise security is still decision-making,” Chenthil said.

As organizations confront increasingly sophisticated cyber threats and expanding AI adoption, the executives agreed that success will depend less on who gathers the most data and more on who can act on it fastest.

In the modern enterprise, seeing everything is no longer enough. The real competitive advantage may lie in deciding what to do next.

Let’s conclude

If enterprise intelligence data could speak, it would probably say “I’ve already found the risks, mapped the threats, flagged the vulnerabilities, and highlighted the Shadow AI problem… now can someone please make a decision?”

In today’s cyber landscape, the real challenge is no longer collecting information, there is already too much of it. The challenge is transforming endless alerts, signals, and dashboards into clear business action before the next Monday morning meeting begins.

The organizations that win will not be the ones with the loudest alarms or the biggest dashboards, but the ones that can turn intelligence into decisions faster than everyone else.

We are in conversation with many solution developers who can fill this GAP by devising a solution which is intelligent, adaptive, predictive story telling model to ease boardroom complexity.

Who are the leaders in this space? Stay tuned for more updates.