Another “bravo” thoughtful piece of content. Inspiration for people like me trying to make this evolution right.
AI’s real impact isn’t in just boosting productivity—it’s in reshaping decision-making at scale. The shift from co-pilot to pathfinder matters. A co-pilot assists; a pathfinder reveals better routes, anticipates roadblocks, and fundamentally changes how we navigate complexity.
I’ve seen this firsthand in PE-backed retail transformation. AI diagnostics uncovered a path to 27% YoY revenue growth—not by just streamlining operations but by reshaping frontline decision-making, revealing hidden opportunities, and optimising real-time execution.
The future isn’t AI assisting us—it’s AI revealing what we wouldn’t have seen otherwise.
You also touch on compensation. Current signals support your argument.
Compensating based on output seems logical—pay for results, not just effort. But the unintended consequence? It rewards short-term efficiency over long-term strategic impact.
When businesses optimise purely for measurable output, they risk:
🔹 Data Blind Spots – Employees shape their work to fit what’s measured, leaving critical but harder-to-quantify contributions undervalued.
🔹 Burnout & Attrition – Productivity at all costs leads to unsustainable work cultures, draining institutional knowledge.
The best compensation models balance performance metrics with adaptability—valuing not just output, but how decisions are made, risks are mitigated, and intelligence is embedded into work.
This is where AI-driven decision intelligence changes the game. Rather than just tracking performance, it:
✅ Maps unseen contributions—capturing the impact of strategic thinking, collaboration, and foresight.
✅ Surfaces better incentives—aligning compensation with value creation, not just volume of work.
✅ Reduces bias—ensuring recognition isn’t skewed towards what’s easiest to measure.
If AI expands how we define productivity, then compensation models can evolve too—rewarding employees not just for what they produce, but for the smarter, more adaptive decisions that drive long-term value.
Curious to hear how others are seeing this shift. How do we evolve workforce incentives to match the complexity of today’s work?
Another “bravo” thoughtful piece of content. Inspiration for people like me trying to make this evolution right.
AI’s real impact isn’t in just boosting productivity—it’s in reshaping decision-making at scale. The shift from co-pilot to pathfinder matters. A co-pilot assists; a pathfinder reveals better routes, anticipates roadblocks, and fundamentally changes how we navigate complexity.
I’ve seen this firsthand in PE-backed retail transformation. AI diagnostics uncovered a path to 27% YoY revenue growth—not by just streamlining operations but by reshaping frontline decision-making, revealing hidden opportunities, and optimising real-time execution.
The future isn’t AI assisting us—it’s AI revealing what we wouldn’t have seen otherwise.
You also touch on compensation. Current signals support your argument.
Compensating based on output seems logical—pay for results, not just effort. But the unintended consequence? It rewards short-term efficiency over long-term strategic impact.
When businesses optimise purely for measurable output, they risk:
🔹 Short-Termism – Incentives drive immediate gains but overlook sustained innovation.
🔹 Data Blind Spots – Employees shape their work to fit what’s measured, leaving critical but harder-to-quantify contributions undervalued.
🔹 Burnout & Attrition – Productivity at all costs leads to unsustainable work cultures, draining institutional knowledge.
The best compensation models balance performance metrics with adaptability—valuing not just output, but how decisions are made, risks are mitigated, and intelligence is embedded into work.
This is where AI-driven decision intelligence changes the game. Rather than just tracking performance, it:
✅ Maps unseen contributions—capturing the impact of strategic thinking, collaboration, and foresight.
✅ Surfaces better incentives—aligning compensation with value creation, not just volume of work.
✅ Reduces bias—ensuring recognition isn’t skewed towards what’s easiest to measure.
If AI expands how we define productivity, then compensation models can evolve too—rewarding employees not just for what they produce, but for the smarter, more adaptive decisions that drive long-term value.
Curious to hear how others are seeing this shift. How do we evolve workforce incentives to match the complexity of today’s work?