Before You Invest in AI, Decide What It’s For
AI has quickly become a fixture in nearly every strategic conversation. It appears in board decks, investor updates, and annual plans with increasing urgency, often framed as both an opportunity and an expectation. In response, many organizations are moving fast — launching pilots, standing up innovation teams, and deploying new tools in visible ways to demonstrate progress. From the outside, this activity can look like momentum. Inside the organization, however, leaders frequently struggle to identify meaningful shifts in performance or outcomes that justify the investment.
This disconnect is becoming harder to ignore. A widely cited analysis from MIT’s Project Nanda found that 95% of generative AI pilots fail to translate into sustained business value. Despite significant experimentation and spend, most initiatives stall before they scale. The challenge rarely stems from the technology itself. More often, it reflects a lack of clarity about what the organization expects AI to actually change.
Before leaders ask how to deploy AI, they need to answer a more foundational question: what is it for? Without a clear purpose, even sophisticated tools tend to amplify existing inefficiencies rather than resolve them. Capability alone does not create direction. It simply accelerates whatever path the organization is already on.
When speed outpaces direction
When AI efforts stall, the underlying causes are surprisingly consistent. Tools are introduced alongside existing processes rather than prompting a redesign of how work should happen. Teams experiment in pockets, disconnected from broader priorities, while governance, decision rights, and accountability remain unchanged. Over time, AI becomes something adjacent to the business rather than embedded within it.
The result is a subtle but important form of drag. Employees experience AI as “one more thing” instead of a better way of working. Leaders see activity but struggle to tie it to outcomes that matter. Initiatives multiply, yet few feel essential. In that environment, adoption slows and skepticism grows, not because the technology lacks potential, but because its purpose has never been clearly defined.
Organizations that make measurable progress tend to take a different path. Instead of asking where they can pilot AI, they start by clarifying which business outcomes truly need to improve and how AI might uniquely enable that change. That discipline can feel slower at the outset, but it creates alignment that allows everything that follows to move faster and with greater confidence.
Purpose protects what makes you distinctive
The importance of this clarity becomes especially visible when organizations adopt AI simply because it is available or expected, rather than because it strengthens their strategy or customer value proposition.
Snapchat’s rollout of My AI offers one cautionary example. The feature was introduced rapidly and prominently, but without a clear articulation of how it enhanced the user experience or supported what people valued most about the platform. Adoption lagged, sentiment declined, and searches for “delete Snapchat” spiked almost immediately. The issue wasn’t the sophistication of the technology; it was the absence of a compelling reason for users to care.
Nordstrom’s Trunk Club tells a different but equally instructive story. Built on a high-touch, personalized styling model, the service introduced automation in ways that improved efficiency on paper but diluted the intimacy that defined the brand. In trying to optimize operations, the organization weakened the very differentiation customers were willing to pay for.
In both cases, AI didn’t create advantage. It blurred it. The technology wasn’t inherently flawed; it simply wasn’t anchored to a clear sense of purpose.
These are the types of dynamics we explored with leaders during our January webinar, Making the AI Vision Real, where a consistent theme emerged: successful AI adoption begins by identifying the specific outcomes that matter most to your organization and your customers. When AI is tied directly to those priorities, it sharpens focus and strengthens performance. When it isn’t, it can quietly erode trust and differentiation. For those who want to explore how to approach this in practice, the webinar recording is available here.
From ambition to operating reality
Defining purpose is only the starting point. The harder work lies in translating that intent into how the organization actually operates.
Many leadership teams articulate a compelling vision for AI, yet struggle to connect that vision to day-to-day behavior. Pilots run in parallel to the business while core workflows, roles, and incentives remain unchanged. Without deliberate operating design, AI remains an experiment rather than a capability.
The organizations that scale successfully treat AI differently. They redesign processes, clarify ownership, and establish governance that supports consistent decision-making. They equip managers to guide their teams through new ways of working and create structured opportunities for learning and adjustment. Instead of asking employees to adopt another tool, they embed AI into the fabric of how work gets done.
This approach requires more intention and coordination, but it is what turns isolated wins into sustainable results.
Leadership is what makes it stick
Even the most thoughtful design will fall short without leadership that reinforces it. Technology cannot align strategy, people, and process on its own. Leaders create that alignment through the expectations they set, the trade-offs they clarify, and the behaviors they model.
As AI becomes more integrated into daily work, the challenge shifts from technical enablement to human adoption. Managers need confidence to guide their teams through evolving roles and responsibilities. Employees need clarity about how their work will change and how they will be supported. Trust must be maintained as the organization experiments and learns. In our experience, this leadership dimension ultimately determines whether AI remains a series of pilots or becomes a durable capability.
That human side of the equation is the focus of our upcoming webinar, Leading the Human Transition, where we’ll explore how leaders build readiness, reduce resistance, and help their organizations adapt as AI moves from novelty to everyday reality.
Purpose is the real differentiator
Access to AI will not be an advantage for long. What will distinguish organizations is the discipline to decide what AI is truly meant to change and the willingness to redesign how work happens in the service of that purpose.
Clarity creates direction. Design turns that direction into action. Leadership sustains momentum.
Before you invest further, decide what AI is for. Everything else follows from there.
Turn your AI investment into measurable results with nepf
Technology is only half the equation. Sustainable impact comes from embedding AI into the way people work, lead, and grow.
Join us for our March 25 webinar, Leading the Human Transition, to explore practical strategies for guiding organizations through the people side of AI adoption and translating AI initiatives into real business outcomes.
If you’re ready to move beyond pilots and turn AI investment into lasting performance gains, we hope you’ll join the conversation.