We've Done This Before: What the Internet and Mobile Taught Us About Positioning AI

Roughly every decade and a half, a technology shift arrives that is large enough to reset customer, employee, and partner expectations of how a company operates. Most leaders today have already managed at least two such transitions.

The commercialization of the internet was the first: adoption was uneven, failure rates were high, and it took years — through the Web 2.0 correction — for norms and best practices to stabilize. The shift to mobile followed a similar arc, compressed into a shorter window, ending with "mobile-first" moving from differentiator to baseline expectation.

AI represents a third such inflection point, and it is moving faster than either of the two that preceded it — a velocity that each prior shift arguably built toward. The internet and mobile transitions gave organizations years to observe, adjust, and eventually articulate a position to their stakeholders. AI is not affording that same runway. As a result, communication is not being neglected so much as displaced: organizations are heads-down on adaptation, and the conversation with the people who depend on them — customers, employees, partners — is being sidelined by necessity rather than by choice.

That displacement is understandable. It is also a risk worth naming directly.

The Gap in Current AI Strategy

Most organizational effort around AI adoption is directed inward: tool selection, workflow redesign, vendor evaluation. This work is necessary, but it addresses only half the problem. The internet and mobile transitions were not purely operational shifts; they were also positioning exercises. Companies were required to articulate, explicitly, how the new capability altered their relationship with the people who depended on them.

AI adoption carries the same requirement, and it separates into two distinct workstreams.

1. Disclosure: Are stakeholders aware AI is in use?

This is not a compliance exercise. It is a trust variable. Customers increasingly assume AI is present somewhere in the products and services they use; the reputational risk is not that they discover this, but that they discover it from a source other than the company itself. A clause embedded in a privacy policy does not constitute communication.

Clear disclosure of where AI is applied — and, equally, where it is deliberately withheld — accomplishes two things: it removes ambiguity that otherwise reads as evasiveness, and it signals an organization confident enough in its methodology to make it visible.

2. Philosophy: Is there a defensible position, and can it adapt?

This is the more consequential of the two. The requirement is not a statement of use ("we use AI") but a statement of reasoning ("here is how we evaluate where and how we use it"). Organizations managing this well are not positioning themselves at either pole — "AI-first" or "AI-averse." They are articulating a position built for revision: deliberate, evidence-based, and structured to adjust as the technology and the norms around it mature.

This is consistent with how well-managed organizations approached both the internet and mobile transitions. Credible companies did not commit to "never" or promise wholesale transformation on an arbitrary timeline. They communicated, instead, that adoption was being managed deliberately, with a stated method for adjusting course as conditions changed.

Why This Belongs in Internal Communication as Much as External

Employees are asking a version of the same questions customers are asking: Is this being deployed responsibly? Does leadership have a defined position? Will decisions affecting their work be made transparently or announced after the fact?

A well-articulated AI position therefore serves two audiences simultaneously. Internally, it functions as a decision-making framework and a source of organizational confidence. Externally, it functions as a trust signal and, increasingly, a point of differentiation. At present, most organizations have neither a stated internal position nor an external one — which is precisely where the opportunity resides.

Operationalizing the Position

A workable AI position does not require a comprehensive public strategy document. It requires clear answers, communicated in plain language, to four questions:

• Where is AI currently applied within the products, services, or processes that customers and employees interact with?

• Where is it deliberately not applied, and what is the rationale?

• What criteria govern the decision to expand AI use into new areas, not simply the intent to do so?

• What remains human-led, and why is that a durable commitment rather than a temporary constraint?

Content built on this framework is durable by design. It is not tied to a specific product cycle or release, and it does not require substantial revision each time the underlying technology shifts, only refinement as the position itself evolves.

Trust Doesn't Wait for Certainty

Organizations are not yet at the stage of this transition where best practices are settled; they are still at the stage the internet occupied in the late 1990s and mobile occupied in the early 2010s: testing, adjusting, and learning in view of their stakeholders. That uncertainty does not preclude clear communication about where an organization currently stands.

The organizations that narrate this transition with clarity, to customers and to their own people, will be the ones retaining trust once the next set of norms is established. The advantage available here is not being first to adopt AI. It is being credible about how.