AI: We Need a Long-Term Lens
Let me be honest – I’m exhausted by the AI hype cycle. Every week, there’s a new game-changer. A model that writes better code. A tool that generates videos from text. A chatbot that supposedly thinks like us. Don’t get me wrong, I’m excited too. I’ve spent years leading digital transformation, and I’ve never seen technology move this fast.
Many organizations are eager to capitalize on AI to achieve efficiency gains. However, an unstructured approach to AI implementation can lead to technical debt, diminished trust, and a failure to realize the full potential of this technology. A strategic, well-planned approach is crucial to successfully leverage AI and avoid potential pitfalls.
But here’s what keeps me up at night: We’re building the plane while flying it, and we’ve forgotten to check if we even want to land where we’re headed.
AI isn’t another tool to plug into a workflow. It’s a fundamental shift in how organizations think, operate, and serve people. And that demands patience.
When I work with teams adopting AI, I ask one question first: Where do you want this relationship to be in three years? Not next quarter. Not after the pilot. Three years.
Because the real value isn’t in automating a report – it’s in reshaping how humans and machines collaborate. It’s in designing systems that grow more helpful, ethical, and intuitive over time. Short-term thinking gives us brittle chatbots and biased algorithms. Long-term thinking builds adaptive intelligence that learns with us, not just for us.
This means investing in:
- People first: Upskilling teams to work alongside AI, not be replaced by it.
- Ethical guardrails: Baking fairness and transparency into systems from day one.
- Iterative learning: Treating AI not as a set and forget solution but as a partner that evolves with feedback.
An organization once implemented an AI assistant with the objective of reducing customer service expenses. While initial results were positive, lasting for six months, subsequent customer dissatisfaction and a decline in trust led to the project’s termination. In contrast, a competitor dedicated 18 months to collaboratively developing their AI solution with frontline employees. This approach has resulted in a well-received system that is continuously refined and fosters genuine customer loyalty.
The difference? One optimized for a spreadsheet. The other is optimized for humans. It means one focused on cost reduction, while the other prioritized the user experience.
AI will reshape our world. Stop measuring AI success by speed alone. Start measuring it by resilience – how well your people adapt, how fairly benefits are distributed, and how much trust you maintain with customers.
Let’s build AI that ages well.