Let’s be honest about year-end reviews: they’re crucial, but they’re often flawed. We sit down, look back, and try to piece together twelve months of decisions. The problem? We all suffer from confirmation bias. We remember the triumphs, and we smoothly explain away the errors. Your traditional review, relying on memory and selective reports, is full of blind spots.
Think of how much better it would be if your review were completely objective, immune to selective memory, and powerful enough to analyse every single piece of data, from that quick Slack message to the vast market report. This is the new reality: the Intelligent Post-Mortem. Artificial Intelligence (AI) isn’t just hype; it’s the tool that’s moving executive review from “I think it worked” to “I know why it worked.”
The clear view: AI against our own biases
Our traditional reviews, while valuable for gathering human insight, simply can’t handle the sheer volume of data we generate today. They usually tell us the result, but they can’t always pinpoint the exact cause. Did that project really succeed because of your strategic pivot, or was the market just having a great quarter? AI solves this by giving you an objective analysis of everything. It meticulously maps your decisions to their actual consequences. It doesn’t judge; it just lays out the complex, evidence-based truth about what happened.
AI’s retrospective toolkit: Three ways it changes strategy
AI doesn’t just grade your performance; it shows you the exact mechanics of your success and failure. Here’s how it works:
Causality mapping: Who gets the credit (or blame)? This is the game-changer. AI uses algorithms to trace the real-world impact of your decisions. You might be celebrating a 10% revenue jump, attributing it to your new marketing staff. But the AI, by looking at global market trends, such as those affecting resource-rich economies like Nigeria, might find that 70% of that boost was due to a rise in commodity prices, making your marketing impact modest. It gives credit where it’s due.
Contextual benchmarking: Were you good, or just lucky? Using the UK as a context, comparing this year to last year is weak. AI compares your company’s performance against the entire business environment. It tells you if your decision was genuinely strategic at that specific moment or if you simply benefited from a rising tide.
Anomaly detection: Finding the hidden gems: Remember that small operational change you made back in May that you completely forgot about? What if it had an explosive, unforeseen impact? AI is brilliant at finding these forgotten actions. It spots statistical anomalies and subtle patterns in the data, perhaps in dynamic, digitally transforming markets like Kenya. It alerts you to risks or tactics that you, or your team, would never catch manually.
Why data matters
Here’s the reality for us: we can’t just copy AI models built in Silicon Valley. Those models don’t understand our market, the informal economy, the unique logistics challenges, or our specific laws, like GAID. To get a beneficial retrospective review, the AI must be trained and validated on our local data. This means you, the executive, have to prioritise data governance. Garbage in, garbage out; it’s that simple. Make sure your data is clean, complete, and relevant to the Nigerian context.
Next Steps: A Practical Action Plan
Adopting AI for these reviews isn’t an all-or-nothing switch. It’s a smart evolution:
Fix your data First: This is non-negotiable. Get your data architecture standardised and reliable. It’s the foundation for everything.
Run a pilot: Don’t overhaul the whole review process yet. Pick one recurring decision, like approving quarterly CapEx, and use the AI retrospective on just that. Prove the value, then scale it.
Demand clarity: Insist on Explainable AI. The system must show you how it arrived at its conclusion. If you can’t understand the “why”, you can’t learn from the insight, and you won’t trust the technology.
Bottom line
We’re moving past guesswork. AI gives you the power to analyse every decision with precision, transforming those dreaded year-end reviews into powerful strategic learning sessions. But here’s the most important part: this isn’t about replacing your leadership or your wisdom. It’s about giving you a super-tool. The smartest executives will embrace a human-AI collaborative approach for their end-of-year review, securing an undeniable competitive edge and building a truly data-driven culture.
Dotun Adeoye is a technology entrepreneur, AI governance leader, and co-founder of AI in Nigeria. He has over 30 years of global experience across Europe, North America, Asia, and Africa and advises organisations on AI transformation, governance, and digital growth.
