Council Post: The Leap To AI Nirvana
Sr. Technical Program Leader at NVIDIA with the mission to deliver velocity and business impact on AI and Strategy-driven programs.gettyNirvana literally means extinguishing something. For the sake of this arti...
Sr. Technical Program Leader at NVIDIA with the mission to deliver velocity and business impact on AI and Strategy-driven programs.
getty
Nirvana literally means extinguishing something. For the sake of this article, "AI nirvana" is when humans don’t have to focus on tasks, and they have the luxury to spend time thinking about the purpose behind the act and making higher-value decisions.
Why is this important? It’s because the more higher-value decisions that get made, the better and faster the leap of innovation and the higher the impact will be. Will this transition to “high-value decisions thinking” be easy? Perhaps not, because the human brain has been rewired over generations to stay focused on tasks and become better at them to achieve productivity gains. While innovation has always been there, the approach that got us where we are today won’t help us make a leap change.
Fortunately, there was always a healthy level of unhappiness with progress that has brought us to the doorstep of AI, where the possibilities can become limitless. AI will help us make the leap.
Enterprises have thus started the amazing, at times feared, and somewhat chaotic progress toward AI nirvana. Discussions in the tech community are all centered around new products, agents, robotics, AI models, the wins and failures of AI and the common blame of how AI will take away jobs, which I am confident will be a myth that will get uncovered soon.
From my seat in the park, I see jobs getting more value-driven and more opportunities to make a bigger impact in the world. In my mind, we are currently in the classic “storming” phase of any change, which will eventually lead us to norming, performing and ending (success).
As enterprises start the journey, the common lesson learned is that AI seldom is the limiting factor; the organization is. A common issue is the lack of a single source of truth; data doesn’t match between teams. Strategy decisions that were well defined in the pre-AI era are now not sufficient as AI can travel cross-functionally.
What then gets illuminated is that the old responsibility and accountability layers don’t function the same anymore. AI solutions are being developed in a siloed fashion and don’t always converge cross-functionally to provide meaningful progress. This then sometimes leads to a “token cost is higher than human cost” kind of erroneous conclusion.
Leaders are being forced to rethink work patterns and decision-making. Technology alone won’t cause the necessary transformation for AI to be a core operational layer. Decision ownership will.
Redesigning Workflows And Execution
Currently, ownership is divided by function. AI, however, has the ability to produce insights continuously and often surface clear cross-functional tradeoffs in real time, yet action stalls because decision ownership is siloed.
When AI is layered onto existing workflow patterns, organizations are left with noise and no impact. This is because AI has the ability to expose gaps in data, decisions and accountability. Automating tasks without redefining decision ownership and workflows gains execution speed but not alignment. The result is speed without direction, and the leadership thus remains constrained.
Companies that do not redesign execution will be left overwhelmed with noise, dashboards and alerts, but no impact.
Actionable Roadmap To Nirvana
The greatest number of models won’t define enterprise success. Intentional impact design will:
• Don't add AI to old processes. Integrate it into the operational layers of planning, execution and governance to drive results that deliver continuous insights. Make decision rights and team structures organic to act on insights quickly.
• Set intent and align teams on priorities and tradeoffs. Impact can be measured through a leap change in customer experience for the better (reducing their cost or providing value never seen before), a leap change in revenue growth for the enterprise or the creation of operational resilience.
• Prioritize impact over action. Make impact quality and velocity (speed with direction) the KPIs.
• Break the silos. Lead the people transition with organic innovation versus organized innovation, as this will promote flexibility and cooperation between teams to support adoption.
The road won’t be easy, as the human brain will need time to rewire to go from task-based thinking to impact-based thinking. However, the more time everyone gets to think, the faster the leap to next-gen innovation will be. Enterprises that adapt to impact-based innovation will lead the leap.
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