Key Takeaways
- AI is compressing time-to-value in resilience programs, shifting the leadership challenge from generating insight to making the right decisions faster.
- Ruthless prioritization is essential as AI expands what’s possible, ensuring teams focus resources on the risks and initiatives that matter most.
- Resilient organizations treat AI as a foundation, not a feature, pairing technology with intentional tradeoffs and disciplined leadership.
Organizations today are operating in an environment that is more complex and less forgiving than ever. From extreme weather and natural disasters to relentless cyberattacks and an ever-complex regulatory environment, even the most mature organizations will be tested in the year ahead.
In a recent episode of the Software Leaders Uncensored podcast, Fusion Risk Management’s CEO, Mike Campbell, offers a timely perspective on what it means to build an organization prepared for the future. The conversation highlights how artificial intelligence (AI) can accelerate time-to-value, enhance situational awareness, and help organizations manage complex risks more effectively.
AI, Simulations, and the Collapse of Time-to-Value
AI-driven simulations are helping organizations prepare for virtually anything, from natural disasters to cyberattacks and everything in between. AI built into the Fusion platform allows customers to:
- Turn static documents into dynamic data to get programs up and running quickly
- Surface and prioritize vulnerabilities ranked by likelihood and severity
- Estimate maximum potential impact
- Shift from reactive crisis management to predictive resilience planning
As AI reduces the time required to understand risk and model outcomes, the bottleneck shifts from generating insights to decision-making. Leaders must then determine which risks, scenarios, and investments truly deserve attention, and which do not.
Ruthless Prioritization: A Core Leadership Discipline
In dynamic environments, especially those reshaped by AI, organizations face more opportunities than they can execute.
The concept of ruthless prioritization encourages teams to:
- Automate routine, manual work, freeing teams to focus on higher-value, strategic initiatives
- Avoid spreading resources thin
- Make intentional tradeoffs
- Maintain clarity around organizational priorities
This discipline ensures that innovation efforts reinforce strategic goals rather than dilute them.
Why Do AI Projects Fail?
“We are sitting on the world’s most massive opportunity for change. Fast movers will be way ahead.”
According to MIT NANDA, 95% of generative AI pilots at companies are failing. But why?
Mike shared his perspective that the high failure rate of early AI initiatives is likely because most organizations are:
- Treating AI as a feature, not a foundation. Many companies are simply adding “AI-powered” widgets, such as co-pilots, auto-summarization, or slightly smarter reports, without rethinking the underlying product or value proposition.
- Underestimating the change in mindset. Working effectively with AI is less like writing a database query and more like building a relationship. It requires rich context, storytelling, and iteration, which are skills that aren’t yet second nature for many teams.
- Reaching opinions too early. People try a model once, hit its limits, and move on, but AI is improving at a pace that makes Moore’s law look slow. A conclusion you reached 12 months ago may already be obsolete.
AI can reveal risks, model outcomes, and remove manual friction, but only ruthless prioritization turns those advantages into results. In an environment defined by constant change, resilient organizations are the ones that prioritize deliberately, act with intent, and stay focused on what enables continuity.
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