At the recent SOMOS Conference in Albany, leaders from across sectors came together for a critical conversation on AI, cybersecurity, broadband, and digital equity—focused on protecting and empowering Latino communities in New York and beyond.
Can Code Communities’ Founder & CEO, Annmarie Lanesey, joined this discussion at a pivotal moment—when the acceleration of artificial intelligence is colliding with longstanding gaps in access, skills, and opportunity.
The central question was clear:
Who has the skills—and the access—to participate in the AI economy?
And just as importantly:
Who does not?
AI Skills Alone Are Not Enough
There is growing urgency to expand AI literacy—and for good reason.
But teaching individuals how to use AI tools without teaching them how to think critically about those tools is not preparation. It is exposure.
In an AI-driven world, individuals must be able to:
- Evaluate outputs for accuracy
- Recognize bias and misinformation
- Ask better questions
- Apply judgment in ambiguous situations
These are not technical skills. They are human skills.
At Can Code Communities, we see this every day. Learners can quickly adopt tools—but without a foundation in critical thinking, communication, and problem-solving, they cannot fully leverage them.
AI skills without human skills will widen the gap—not close it.
Human Skills Are the Differentiator
As AI becomes more accessible, the ability to use it effectively will depend less on access to the tool—and more on the ability to interpret and apply it.
Critical thinking, adaptability, emotional intelligence, and communication are becoming the defining skills of the AI era.
These are the skills that:
- Prevent individuals from being misled by AI outputs
- Enable creativity and innovation
- Allow workers to collaborate with, rather than be replaced by technology
Yet these skills are often underprioritized in traditional training models.
That must change.
Access Remains the Greatest Barrier
While conversations about AI accelerate at events like SOMOS, many individuals are still navigating more fundamental challenges:
- No device
- Unreliable or no internet access
- Limited or no foundational digital skills
For these individuals—many from historically underserved communities—the AI economy is not just out of reach. It is invisible.
This was a central theme of the SOMOS discussion: without intentional strategies to reach Latino communities and other underrepresented populations, the benefits of AI will not be equitably distributed.
At Can Code, we work with learners starting from this exact place. And we know that with the right support—devices, connectivity, training, and coaching—they succeed.
But without sustained investment, these individuals will remain excluded from the fastest-growing segment of the AI economy.
Access is not a secondary issue.
It is the entry point to everything else.
The Risk: A Two-Tiered AI Economy
What is emerging is a two-tiered system within the AI economy:
- Those with access + AI skills + human skills → accelerating into higher-wage, future-proof careers
- Those without → falling further behind, with fewer opportunities to catch up
This is not just a workforce issue.
It is an economic mobility issue within the AI economy.
And it is happening now.
Aligning Training, Access, and Opportunity
The discussion at SOMOS reinforced that solving this challenge requires more than isolated efforts.
It requires alignment:
- AI Skills → ensuring individuals can use emerging tools effectively
- Human Skills → ensuring they can think critically, communicate, and adapt
- Access → ensuring they can participate in the AI economy at all
At Can Code Communities, this is the model:
Provide devices and connectivity → build foundational digital skills → introduce AI literacy → connect to career pathways.
When these elements come together, the results are transformative.
What Must Happen Next
If there was one clear takeaway from SOMOS, it is this:
The market alone will not solve this.
To ensure an inclusive AI economy, we need coordinated action:
- Public investment in digital access, skills training, and AI literacy
- Employer engagement to create real pathways into jobs
- Community-based organizations funded to operate at scale
- Education systems that embed both AI and human skill development
Without this, the gap within the AI economy will continue to widen.
Conclusion: A Defining Moment for the AI Economy
The AI economy is not coming—it is already here.
The question is whether we will build systems that allow everyone to participate—or only those already positioned to succeed.
AI skills matter.
Human skills matter.
Access matters.
The conversation at SOMOS made one thing clear: without all three, opportunity within the AI economy remains out of reach for far too many.
At Can Code Communities, we are working every day to bring these pieces together—because participation in the AI economy should not be determined by where you start.
To learn more or enroll in our Spanish-language digital and AI skills training program, visit: https://cancode.org/course/ai-essentials/