The AI Divide Is the Next Economic Divide
Can Code Communities’ Founder and CEO, Annmarie Lanesey had the honor to speak at Connected America alongside leaders from across the country on a defining issue of our time:
Who will participate in the AI economy—and who will be left out?
The answer is already emerging. And it should concern all of us.
The AI Gap Is Not Technical—It Is Structural
The dominant narrative suggests that the primary challenge of the AI era is technical upskilling.
That is incorrect.
The most immediate gap is human: the ability to question outputs, assess accuracy, and apply judgment in an environment where information is instant, abundant, and often flawed.
We are producing users of AI tools faster than we are producing critical thinkers.
Without intervention, this will not just limit opportunity—it will degrade decision-making at scale.
The Digital Divide Has Evolved Into an AI Divide
For years, we have framed digital equity as a question of broadband access.
That framing is now outdated.
Across communities, individuals still lack devices, reliable connectivity, and foundational digital skills. They are not simply behind—they are excluded from the starting line of the AI economy.
At the same time, institutions and corporations are rapidly embedding AI into workflows, accelerating productivity and redefining work itself.
The result is a widening asymmetry:
- Those who can leverage AI are compounding advantage
- Those without access or skills are falling further behind
Digital equity and workforce development are not parallel efforts. They are the same system—and it is currently misaligned.
We Are Undervaluing Nontraditional Workforce Pathways
The current workforce infrastructure is not designed for the speed or scale of this transition.
Community-based training organizations, community colleges, libraries, and local partners are doing the most adaptive, responsive work in this space—yet they remain underfunded and under-leveraged.
These institutions are not supplemental.
They are foundational to building an inclusive AI workforce.
If we fail to invest in them, we are choosing to narrow the pipeline by design.
Market Forces Alone Will Not Solve This
There is a persistent assumption that the private sector will naturally reskill the workforce as AI adoption increases.
There is little evidence to support this.
If left to the market:
- Investment will concentrate where return is immediate
- Upskilling will prioritize those already positioned to succeed
- Entire populations will remain excluded
This is not a hypothetical risk. It is already happening.
A Coordinated Response Is Required
Addressing the AI divide requires intentional alignment across sectors:
- State governments must invest directly in digital skills and AI literacy as core economic infrastructure
- Corporations must move beyond pilot programs and commit to sustained, place-based investment
- Community-based organizations must be funded to operate at scale, not at the margins
Waiting for federal intervention or market correction will only widen the gap.
Proof of What Works
We have already seen what is possible when access, training, and opportunity are aligned.
A veteran, unemployed for nearly a decade, received training and a device through Can Code. Within a year, he secured a role at Accenture earning over $100,000.
This is not an outlier.
It is a model.
The constraint is not potential.
It is investment and scale.
The Defining Question
There is a growing belief that future economic value will be tied to how effectively individuals can leverage AI—how many systems they can deploy, manage, and integrate into their work.
If that is true, then access to AI literacy and digital skills is no longer optional. It is determinative.
We are not just shaping a workforce transition.
We are shaping the distribution of opportunity for the next generation.
Conclusion: The AI divide is not inevitable.
The AI divide is not inevitable. It is the result of decisions—about where we invest, who we prioritize, and how we define workforce readiness.
We can continue to treat digital equity as a secondary issue.
Or we can recognize it for what it is:
Core economic infrastructure in the AI era.
The window to act is narrowing.
