AI is the latest corporate cure-all. Just sprinkle some over your business, and inefficiencies vanish. At least, that’s the pitch.
Everyone from academics and government bureaucrats to consultants, seasoned practitioners, casual observers, and the local conspiracy theorist has an opinion on its transformative power. Digital transformation discussions obsess over AI, treating it as a magic elixir capable of solving all operational woes.
The advice is often generic, but sound: define objectives, assemble teams, allocate resources, identify use cases, research the best tools, establish a process to scale successful experiments, and so on. Logical steps, but there’s a crucial caveat beyond the difficulty of execution: the false assumption that ‘business as usual’ can be improved with a few AI tools.
The gravitational pull of the status quo is underestimated. Many assume that AI’s elegance and utility will naturally override entrenched habits and outdated processes.
It won’t.
Change doesn’t happen because of technology; it happens because there’s an undeniable, compelling reason to shift. That reason must be powerful enough to overcome the inevitable resistance. The benefits of change are often broad and enterprise-wide, but the costs, both real and perceived, tend to be personal, creating the very resistance that stalls progress.
No matter the size or urgency of the change, the Theory of Constraints applies.
The speed of any process, including transformation, is determined by its biggest bottleneck. Identify the constraint, remove it, and then tackle the next biggest friction point. When the constraint is culture, the weight of the status quo, and the psychological safety of individuals, change demands a different approach. To be successful, it must be driven by empathy, engagement, and a keen understanding of what’s really at stake for the individuals at the ‘coalface’ of the change.
The compounding effect of small but continuous improvements is what drives real progress. Rinse and repeat, again, and again.
Used tactically, AI is enormously valuable now and will only accelerate in importance.
I have a three-part mantra for tackling bottlenecks: Automate, Delegate, Eliminate.
AI excels at all three. It automates processes, enables and manages delegation (sometimes through outsourcing), and eliminates inefficiencies by delivering transparency and reducing waste.
However, AI alone is not enough. Re-engineering a process is not about throwing technology at a problem. It requires leadership, a deep understanding of why bottlenecks exist in the first place, and the willingness to take decisive, sometimes radical, action.
The brutal truth: AI doesn’t make bad decisions good, lazy leadership effective, or broken cultures functional. It just automates the mess faster. If organizations don’t adapt, if people, workflows, and mindsets don’t shift, then AI will be nothing more than an expensive distraction.
To truly reap its benefits, businesses must not just implement AI but also create an environment where it can thrive. And that demands real leadership. AI does not lead, it can only go where directed, led to the situations where its ability can be leveraged. If leadership is missing, all AI does is magnify and accelerate the impact of the problems, creating uncertainty on the way.
