The Last Mile Is Still Human!
One month since launch and 2000 unique visitors from 30 countries, including the US, UK, Netherlands, South Africa, Australia, and India. There are billions of websites, but you chose to visit readintersections.com. Thank you for choosing to include us in your learning path. This encourages us to keep going on our mission:
to capture and curate first-hand operating wisdom from CXOs, Founders, and Senior Leaders, and make it genuinely useful to peers.
Every month, we aim to surface a pattern emerging from the views our authors share. It's not surprising that AI is central to most articles. Across the stories that we recently published, one pattern repeats: AI compresses the learning loop but doesn’t complete the last mile. It speeds up sensing and analysis, but outcomes still depend on judgment, trust, adoption, and follow-through.
A telecom leader described how his teams used to live by “fail fast.” When AI can flag issues in near real time, waiting for failure makes no sense. Engineers now fix problems before anyone logs a ticket. Customer signals that once took months now show up in days. But the limits are clear. AI can predict churn and surface patterns. A leader still has to decide what to do and understand what’s really driving disengagement. This gap also appears in preventive child health. Schools using digital health passports catch anemia and vision problems early, before they affect learning. But the last mile remains human. Technology can recommend interventions, but cannot earn a doubtful parent’s trust or ensure a child wears glasses daily. In education, the point is stark: as one EdTech leader said, the best technology is the one teachers actually use.
Once you observe this “last mile” theme, you start seeing it beyond AI too. Wars in Ukraine and the Middle East have disrupted the supply chains, energy costs, and investment decisions. A clean energy leader building EV infrastructure described the current market moving faster than planned, forcing a shift from proving the concept to running it at scale daily.
Net, net, AI speeds up the analysis. But the execution, the judgment call, the work of actually changing how people behave, that still sits with humans. What makes human decision-making harder right now is that it is being exercised in genuinely difficult conditions.
That is exactly why this platform exists. Not to document what worked in stable times. But to capture how leaders think and decide when the ground is moving under them.
To every author who contributed this month, thank you. You didn't just share what went well. You shared where things got hard, where the plan hit a wall, and what it took to make a call anyway. Those are the moments worth writing about.
Read. Reflect. Share. We are just getting started.