The Last Mile of AI Is Organizational

For the past several years, organizations have been asking an important question: How do we adopt AI?

But I think the more consequential question is becoming: What kind of organization does AI require us to become?

I'm certainly not alone in thinking this way. There is growing recognition that many of the barriers to realizing value from AI aren't purely technical. They are also organizational including governance, workflows, data, decision rights, workforce capabilities, leadership alignment, trust, and change, among others. I agree with that assessment, but I also think we need to take the conversation one step further.

If the last mile of AI is organizational, what exactly is it about the organization that gets in the way? 

I believe the deeper issue is structural. For example, organizations are generally managed in functions, but they perform as systems. Moreover, organizations create strategies at the enterprise level, allocate budgets through functions, assign accountability within departments and measure performance through functional KPIs. Individual functions may also have strategies of their own. 

Enterprise performance depends not only on what happens within functions, but on the interactions and dependencies between them. A decision made in Finance can affect Operations. A workforce decision can affect customer experience. A contract negotiated by Legal can constrain Technology. A technology decision can create new responsibilities for HR, Risk, Finance and frontline employees. Then, AI enters this already interconnected environment and can accelerate the decisions, workflows and processes moving through it. And that's consequential.

As AI influences more decisions and processes that cross organizational boundaries, the effects of those decisions can propagate across the enterprise. What works within one function can create friction somewhere else. So an organization can have excellent AI technology, talented people and a sound strategy and still struggle to translate its AI investment into enterprise value. The technology may work while the organization around it does not work well enough together. That's what I mean when I say the last mile of AI is organizational.

AI can generate value in particular use cases while the enterprise still struggles to scale and coordinate that value. The next phase of AI maturity, in my view, won't be defined simply by who adopts the most AI. It will be defined by which organizations understand and strengthen the organizational conditions that allow human judgment, technology, governance, data and execution to work together reliably. That’s because these organizational conditions predate AI. AI exposes them, interacts with them and, under some circumstances, amplifies their consequences.

I've spent much of my career working across organizations from very different vantage points including technology, law, finance, operations, HR, sales and customer experience. What increasingly interests me isn't only what happens inside any one of those functions. It's what happens between them. Because that's often where risk hides. It's also where value gets lost. And as AI becomes business as usual, those seams are going to matter even more.

The last mile of AI isn't technological. It's organizational. And I think we're only beginning to understand what that really means. #AI #AIRisk #AIGovernance #KPI #ROI #Data #Analytics #AIStrategy #LeadershipAlignment #RiskManagement #EnterpriseValue #OrganizationalSafety