Hiring For Critical AI Roles? 20 Factors To Consider When Starting
In recent years, artificial intelligence has transitioned from an emerging technology to a tool that’s deeply embedded in business operations across industries. As AI becomes increasingly central to operations, hiring processes and the capabilities of current and future employees will play a key role in how well a company is able to navigate a rapidly changing business environment.
Between data scientists, prompt engineers, AI engineers and more, it can be difficult to identify which position(s) will best serve a company as tech tools and needs constantly evolve. Below, 20 Forbes Business Council members detail factors businesses should consider when determining which roles are most critical to hire for first.
1. The Problem At Hand
As AI becomes core to operations, the real question isn’t which AI role to hire first; it’s what problem you’re solving. Most companies don’t need full-time specialists yet. What works far better is a flexible bench of AI contractors who bring diverse skills and adapt fast. AI rewards agility, so your people model should, too. - Marshall Morris, HomeLife Brands
2. Mission And Cultural Alignment
The first factor to consider when determining roles around AI is to determine how AI will align with the organization’s mission and culture. Once alignment is confirmed, the first position can be determined by its impact on the way AI will drive the organization to accomplish its goals while maintaining cultural alignment. - Matthew Davis, GDI Insurance
3. The Desired Impact
Titles matter far less than the person in the seat. The leaders who shape this transformation will bring clear judgment, humility, encouragement and a creative approach to using AI instead of just an efficient one. Any role can have an impact, but who you hire determines whether that impact will be lasting, positive and scalable beyond your early adopters. - Allison Williams, idealis advisory
4. Immediate Needs And Long-Term Goals
When hiring AI roles, companies should balance immediate operational needs with long-term strategic goals, especially if they lack existing AI experience. It’s important to prioritize roles like prompt engineers or data scientists, blending specialists and generalists who can deliver quick value while also building foundational capabilities. This ensures rapid impact and sustainable AI growth. - Annie Phan, Diligent Corporation
5. The Ability To Balance AI Capabilities And User Needs
Roles that can translate between what AI is capable of and what users need are often more critical early on than specialized knowledge or titles, because these employees ensure the AI technology is actually solving user problems. Most companies benefit from using AI technology that already exists and applying it to their problem set rather than building brand-new models from the ground up. - Sara Mauskopf, Winnie
6. The Need For A Tech Strategy
I’m seeing an influx of technology managers being hired to help implement a technology strategy that includes AI. This was the best decision I made in 2025, and I believe it’s important for small businesses, too. This role would incorporate multiple areas, and since you shouldn’t bite off more than you can chew, having at least one person who is focused on this and has time to keep up with the changes is essential. - Cindy Free
7. Risk Gaps
Start with the role that closes your biggest risk gap. For example, if your challenge is data quality, start with a data scientist. If your problem is safe deployment, hire an AI ethicist. If it’s adoption, focus on prompt engineers. The critical hire is the one who turns AI from a concept into a reliable and accountable value for the business. - Aaron Dhaliwal, avua
8. Direction
Hire for roles that protect direction, not just data. Tools are useless without clarity. AI ethicists and prompt engineers matter, but the real priority is whoever can turn AI into better decisions. Lead with strategy, then stack the talent. - Michael Lanctot, YoungNRetired
9. Clarity About Governance
Having clarity about governance is essential for all stakeholders to avoid unproductive work. Outsource the services these professionals provide first! Once you understand the role of each in the context of your governance plan, you can avoid misfires and prioritize which roles to fill first. - Jim Owens, West Texas National Bank
10. Change Management Strategies
An effective AI strategy starts with change management. Rather than focusing on hiring engineers or ethicists, focus on your team. Operational improvements are dependent on understanding the impact on people and gaining their buy-in. - Lee Shapiro, 7wireVentures
11. Accountability For Business Impact
One key factor is where accountability for business impact sits. The first critical hire should be someone who can translate AI into decisions, workflows and measurable results, not just build models or prompts. Without clear ownership, AI stays theoretical. Specialized roles matter later, but impact-driven integration must come first. - Vazgen Harutyunyan, ELDORADO (Elmarket LLC)
12. Potential Mistakes
First, think about what happens if AI messes up. For example, in the medical or legal field, an incomplete answer will cause problems—what then? AI is not magic but a set of many “if-then” statements. There must be checks, a minimum of improvisation and very clear data. I would start with security and the legal part. - Mykola Lukashuk, Marketing Link LLC
13. Adaptability
This may not hold true for mature companies, but I believe adaptability is a key factor at an early stage. Early teams should hire for fluid intelligence, meaning people who can both build and translate business problems into products, because the AI stack, use cases and constraints are still evolving. - Aman Mishra, Unsiloed AI
14. Decision Quality Improvements
Hire for the role that improves decision quality first. AI creates output fast, but bad inputs and unclear guardrails break everything. A strong AI strategist or data lead who understands the business can shape prompts, policies and models in a way that drives real outcomes. Without that foundation, specialist roles never compound. - Justin Inman, emberos
15. Shared Responsibility
Do not start with roles. We saw this with IT, and it resulted in tasks being set off to the side while the business sent in requests. Today, every leader is expected to be IT fluent, and AI is the same. The critical move is to ensure that every hire in every role already knows how to use AI in their function. - John Palinkas, Institute for Digital Transformation
16. Adoption
Start with whoever owns adoption, not just implementation. Technology doesn’t fail; adoption does. The systems I contributed to over four decades worked because someone owned the bridge between technology and people. Your first AI hire should do the same. Understand your operations and drive adoption; don’t just build models. - Donna Mitchell, Mitchell Universal Network, LLC
17. The Need For A Broad Internal Ecosystem
Whether the role is hired from the outside or onboarded from within, it is crucial to have an AI strategist in place to ensure that the company’s AI tools and platforms interlink as part of a broader internal ecosystem. Otherwise, you risk creating what I call “AI orphans.” These are AI outputs that lack the purpose or integration that guide those outputs toward real impact and tangible outcomes. - Sal Fuentes, Decision Counsel
18. Centralized, Clean Data
We believe there are three critical components to creating great AI solutions: customers, domain expertise and data. The first two are hard to create, as you either have them or you don’t. The third component, data, is a real investment—you have to maintain centralized, normalized, clean data so your AI solutions can take advantage of every aspect of your operations. - Andrew Stern, Quilt Software
19. The Bottom-Line Impact
Businesses need to ensure they have a clear understanding of how each hire will affect their bottom line before sending out an offer. Get really clear about the gaps on your team, especially those that are slowing down revenue-generating projects. Start there. - Emily Reynolds, R Public Relations
20. Scalability
I always start with roles that directly impact business scalability. For example, when expanding FeedUp in Uzbekistan, we prioritized operational analysts who could translate AI insights into actionable decisions. Focus on those who are optimizing delivery, inventory and customer experience. - Diana Kurbanova, UzFranchise
Read original post here.
by Admin
Comments