You can’t predict the future. You can build the fitness to respond to it. #MindCandy is fuel for strategic conversation about what’s next.
Three ways operational debt will break your AI strategy, and how to recover
Three types of operational debt compounding beneath AI deployments.
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Technical debt — manual steps and outdated tools that were never cleaned up.
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Integration debt — AI tools dropped into siloed environments where signals can’t be correlated.
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Human-AI partnership debt, where nobody has defined which decisions belong to machines and which belong to people.
84% of companies have already experienced at least one AI-related outage. Yet, most are still managing those failures with processes built for a slower, human-first era. The financial stakes make this untenable: 68% of organizations lose more than $300,000 per hour when systems go down. And as AI complexity grows, the blast radius of each failure grows with it.
https://thenewstack.io/operational-debt-ai-strategy/
The leadership question
If your most important AI-enabled workflow failed tomorrow morning, who would know first, who could stop it, who owns the decision, and how far would the damage spread?
Run an AI blast-radius audit. Map critical workflows, data sources, APIs, vendors, approval points and customer touchpoints. Define owners, escalation rules and kill switches. Simulate failure.
The other prompts:
Free downloads
12 free books on strategy, innovation, intrapreneurship, AI, future trends and leadership. Each one distils the best thinking from dozens of business books into a single, actionable read. Every book is also available as a BookBuzz session, board briefing or keynote.
Data Transformation Is the CEO’s Business
A massive, multiyear initiative to transform corporate data at Caterpillar demonstrates what top executives must do to unlock the power of their data assets.
https://sloanreview.mit.edu/article/data-transformation-is-the-ceos-business/
Making Marketing More Modular: What Agentic AI Can Learn From The Shipping Container Revolution
Relevance, freshness, rights, cost and geographic validity matter for more than sheer scale. Marketers should interrogate whether the data their agency delivers truly outperforms their existing baseline. A black book mentality seeks to orchestrate the right data for clients, not to meet a platform payback requirement. Also check out: https://www.ronimmink.com/project-management-wisdom/
How Will AI Change Software Organizations?
AI is fundamentally changing how software companies build, run, sell, and maintain software. The biggest impact will be felt by engineering and go-to-market organizations, where most of the headcount sits
https://www.bain.com/insights/how-will-ai-change-software-organizations/
After AUtomation
AI commoditizes the residue of human expertise—whatever can be made explicit enough to train on. That collapses the value of default model output and creates demand for what’s different. Demand for what’s different is demand for human experts, even as we approach artificial general intelligence
https://every.to/p/after-automation
AI needs more than intelligence—it needs humanity
AI won’t make organizations less human—but it will raise expectations for how people think, decide, and work. The organizations that succeed won’t be the most automated. They’ll be the ones that invest in people as intentionally as they invest in technology.
From “What Happened?” to “What Will Happen?”
Bringing Predictive Intelligence to Conversational BI
https://www.databricks.com/blog/what-happened-what-will-happen
AI Should Meet Data, Wherever It Lives
“AI Anywhere,” an open hybrid data and AI platform that enables organizations to deploy AI models wherever their data lives.
https://www.cdotrends.com/story/5034/ai-should-meet-data-wherever-it-lives
