Future-proof Your Organization: Emerging AI Talent for Every Function

The World Economic Forum’s Future of Jobs Report 2025 states that 86% of survey respondents expect AI and information processing technologies to transform their businesses by 2030. 

You’ve heard it before, the rise of artificial intelligence (AI) is transforming industries at an unprecedented pace — from marketing and healthcare to education and customer service. As companies race to integrate AI, they often overlook one of the most critical factors to overall success in an “Intelligent” Organization: the non-technical talent. 

According to a report by Lightcast, in 2024 over half of job postings requesting AI skills were outside of IT and Computer Science. Yes, machine learning engineers and data scientists are vital. But so are the professionals who shape, guide, and scale AI systems without writing a single line of code. In fact, futureproofing your organization means recognizing that human-centered, non-technical AI roles are just as essential to innovation, trust, and impact.

Ignoring AI's non-technical aspects is a strategic misstep, especially since over half of AI-related job openings are for non-technical roles. Since 2022, there's been an 800% increase in non-IT generative AI positions, indicating that AI proficiency is becoming fundamental across all departments. From marketing teams utilizing AI for content generation to HR departments employing predictive analytics for talent acquisition, the widespread adoption of AI across various career fields signifies a fundamental market shift rather than isolated trends. 

While we know roles are changing with the adoption of Generative AI, what jobs are emerging due to the AI revolution? Let's take a look at the non-technical AI roles you may need to add to your team.

What Is Non-Technical AI Talent?

Non-technical AI talent refers to professionals who work in the field of artificial intelligence (AI) but do not build or program AI systems themselves. Instead, they contribute in areas like strategy, ethics, operations, communication, design, policy, and more—playing critical roles in ensuring AI is developed, adopted, and governed responsibly and effectively. Here are just a few examples:

Why These Roles Matter

Hiring non-technical AI talent isn't just about filling operational roles; it's about building a robust, resilient, and responsible AI strategy. These resources bring crucial perspectives and skills that directly impact the efficacy, ethics, and ultimate success of your AI initiatives. Here’s why these types roles are key to your future success: 

1. Bridging Business & Tech
   These professionals translate AI output into business insights, ensuring tools meet real needs.
2. Ethical Guardrails & Governance
   Non-technical roles handle biases, privacy, and regulatory compliance—reducing legal risks and building trust.
3. Human-Centered Innovation
   Diverse perspectives and domain expertise lead to more inclusive AI design.
4. Building Trust & Adoption
   Trainers, educators, and CSMs ensure end-users understand and embrace AI tools.

Bonus: Human Skills are Still Coveted for AI roles 

Across all job postings that mention at least one AI skill, a clear hierarchy of capabilities emerges. The data reveals which skills employers consistently value when they’re building AI-enabled teams. 

The pattern is striking: only two of the top ten skills are actually AI-specific capabilities. 

Human skills dominate even in roles explicitly seeking AIexpertise, challenging the assumption that AI jobs are purely technical endeavors.When employers build AI-enabled teams, a clear hierarchy of valued capabilities emerges from job postings mentioning AI skills. The data reveals a striking pattern: human skills dominate, with only two of the top ten skills being AI-specific. This challenges the assumption that AI jobs are purely technical, even in roles explicitly seeking AI expertise. 

According to LightStream, of the growing number of posts that specifically outline AI skills, these are the top ten skills employers are looking for: 

• Communication: the ability to effectively interact, convey information, and collaborate with others in a clear and understandable manner.
• Artificial Intelligence: the development of algorithms and models that enable machines to perform tasks such as learning, reasoning, problem-solving, and understanding natural language.
• Management: a set of skills that involve a variety of tasks, such as planning, organizing, leading, and controlling resources to achieve specific goals.
• Operations: a fundamental skill that involves managing and overseeing the day-to-day activities of a business or organization. 
• Leadership: a skill that involves the ability to motivate and guide a team towards achieving common goals.
• Research: a skill that involves gathering and analyzing information to answer questions or solve problems. It involves identifying reliable sources of information, evaluating the credibility of those sources, and synthesizing the information to draw meaningful conclusions.
• Machine Learning: a subset of artificial intelligence that involves the development of algorithms and statistical models that enable systems to perform tasks without explicit instructions.
• Customer Service: a necessary and common skill in almost every field and industry. It involves effectively communicating with customers to understand their needs, answering their questions or concerns, and providing them with excellent support and service.
• Writing: a skill that involves putting thoughts and ideas into words through the use of language. It is an essential communication tool used to convey messages, express thoughts and emotions, and share information.
• Problem Solving:  the process of identifying, analyzing and resolving problems that can arise in any situation. It involves identifying the root cause of a problem, generating possible solutions, evaluating those solutions and implementing the best one.

This skills profile reveals the fundamental nature of AI-enabled work. Technical AI capabilities provide the foundation, but success depends on workers who can apply these tools strategically, communicate insights effectively, and solve problems requiring both human judgment and machine capability. 

Inclusive Hiring = Better AI

“Inclusive hiring” means designing hiring practices so that people from diverse backgrounds (gender, race/ethnicity, socioeconomic status, education, disability, neurodiversity, etc.) have fair and equal access, and are evaluated in ways that reduce systemic bias.

Some reasons inclusive hiring for AI talent is especially important:

1. Bias in AI systems: AI systems are often trained on data with bias. Having more diverse teams helps in spotting, mitigating, and correcting those biases.
2. Better problem solving: Diverse teams tend to produce more creativity, better performance, and can address broader real‑world use cases.
3. Fairness and regulation: There are increasing legal, ethical, and reputational pressures to make sure hiring (especially with AI tools) is fair and non‑discriminatory.
4. Broader talent pool: Restrictive hiring criteria (elite degrees, past employer pedigree) leave out many capable people. Inclusive hiring expands options.

While inclusive hiring has big upsides, there are many pitfalls, particularly in AI talent acquisition and evaluation. One major risk is algorithmic bias, where AI tools trained on historical data may unintentionally favor certain groups, reinforcing discrimination based on race, gender, or educational background. Many of these systems also lack transparency, making it difficult to understand or audit how decisions are made. 

Because AI is changing the face of the workforce quickly, most in-demand AI roles are perfect for professionals looking to pivot — especially those returning to work or coming from adjacent industries. Skills in project management, education, policy, operations, or communications are highly transferable in the AI space. But, many hiring processes often rely too heavily on traditional credentials, excluding capable candidates from non-traditional paths. Without proactive bias auditing and human oversight, these systems can entrench inequity rather than promote inclusion.

Platforms like The Mom Project, with algorithms optimized to not exclude anyone based on any sort of bias, are ideal for connecting companies with this often-untapped talent pool, ready to help you future-proof your organization. For example, we have 189,630 candidates with Non-IT AI skills in our talent network, most of whom would be weeded out by other algorithms due to gaps in their resume  from caregiving responsibilities. 

How to Start Hiring AI Talent Today

AI has been coined the Fourth Industrial Revolution; Now employers need workers who can effectively integrate AI tools into existing workflows, communicate AI-generated insights to stakeholders, and manage teams that include both human workers and AI systems. Take these steps to assess your current organization and determine where to begin to add AI talent: 

1. Spot Your Gaps — Audit your teams: Are outputs reviewed? Is bias tracked? Are users supported? Do you have the non-technical talent to ensure success? 
2. Write Job Descriptions with Candidates in Mind  –  Seek skills, not credentials. For example: “Detail-oriented reviewer” vs. “5+ years Python”. Remember, you don’t need a unicorn, you might just need a mom. 
3. Use Diverse Hiring Channels — Tap into return-to-work platforms, interdisciplinary talent pools, and most importantly, The Mom Project, where real humans are reviewing every application and reading between the lines for you to ensure applicants really have the skills that mean success. 

Remember, AI Success Is Human Success

Yes, AI is powered by technology and algorithms, but it's driven by people. Your organization’s AI future depends just as much on who you hire as what you build. By investing in non-technical AI talent—from marketers to trainers and prompt engineers to ethics leads, you not only future-proof your technology, but also your teams, culture, and your bottom line.

If you're not hiring non-technical AI talent, you're not AI-ready. The Mom Project connects you with exceptional non-technical talent ready to power your AI transformation. From returning caregivers to career pivoters, our network delivers the insight, adaptability, and values-driven impact your teams need now.

Ready to build smarter, more inclusive AI?
Partner with The Mom Project to hire your next non-IT AI change-maker today.