Should You Hire AI Talent or Use an AI Consulting Team?

As AI becomes a bigger business priority, leaders have to decide how they’ll build the expertise to support it. 

For some organizations, the answer is hiring AI talent that can become part of the team and build long-term capabilities internally. For others, the work calls for an AI consulting team with the mix of strategy, technical expertise, governance, and implementation experience needed to tackle a defined initiative. In many cases, companies may need some combination of both. 

Choosing the right approach starts with understanding the work ahead, the expertise you already have, and what you need your investment to accomplish. 

What AI Talent Are Companies Hiring? 

AI talent covers a wider range of roles than many organizations realize. Some professionals build models and applications, while others focus on the data, infrastructure, governance, or product strategy needed to make AI useful within a business. 

Depending on the organization and initiative, an AI team could include: 

• AI engineers 
• Machine learning engineers 
• Data scientists 
• Data engineers 
• MLOps engineers 
• AI/ML architects 
• AI product managers 
• AI governance and responsible AI specialists 
• AI automation consultants 

Demand for these capabilities is growing. LinkedIn’s September 2025 labor-market update found that AI engineering hiring had increased more than 25% year over year. AI engineering jobs also represented nearly 7% of technical job postings on LinkedIn, while AI talent represented less than 1% of LinkedIn members.

For leaders, that makes defining the actual capability you need especially important before opening a role. 

When Does Hiring AI Talent Make Sense? 

Hiring AI talent can be a strong fit when AI will be an ongoing capability your company wants to own internally. 

Maybe you’re building an AI-enabled product that will continue evolving. You may already have mature data and engineering teams but need an AI engineer or architect with specialized expertise. Or perhaps you’re building an internal AI function that will support multiple parts of the organization over time. 

Bringing AI professionals in-house can help companies: 

• Build institutional knowledge around AI 
• Integrate AI expertise into existing technology and business teams 
• Develop capabilities the organization will need long term 
• Maintain internal ownership as AI initiatives evolve 

Strong AI talent still needs the right environment around it. Leaders should consider whether the organization has clear ownership, technical infrastructure, priorities, governance, and complementary skills to help new hires succeed. 

When Does an AI Consulting Team Make Sense? 

Sometimes the need is bigger than an open position. 

An organization may have a specific AI initiative it wants to execute but lack several capabilities required to deliver it. A project could involve business strategy, data, engineering, governance, implementation, and organizational change, for example. 

Those circumstances can make AI consulting services a better fit than trying to hire every capability individually. 

A consulting approach may make sense when: 

• The company has a defined business or technology problem to solve. 
• Several specialized capabilities are needed at once. 
• Internal teams don’t currently have the necessary AI expertise. 
• The organization needs help identifying or prioritizing appropriate AI use cases. 
• The work has specific deliverables or outcomes. 
• The organization needs coordinated expertise across business and technology functions. 

The broader organization matters here, too. Microsoft’s 2026 Work Trend Index found that organizational factors such as culture, manager support, and talent practices accounted for twice the reported AI impact of individual factors.

IBM’s 2026 CHRO Study found that only 26% of surveyed organizations clearly define work across human-led, AI-assisted, and AI-executed activities. [ibm.com] 

Taken together, those findings are a useful reminder for leaders to think about AI as an organizational capability, including the people, processes, and structure around the technology. 

How Much Should AI Salaries Factor Into the Decision? 

Cost will naturally be part of any build-versus-consult conversation, but salary alone doesn’t tell leaders what an AI capability will cost. 

An AI initiative may require several specialties. Organizations should consider the number and seniority of professionals required, how long they’ll need those skills, their geographic market, and which complementary capabilities already exist internally. 

Insight Global’s 2026 AI Salary Guide can help leaders benchmark compensation while evaluating their talent strategy. 

According to our salary guide, the median annual salary is $150,000 for an AI Engineer, $155,000 for an AI Product Manager, and $180,000 for a Machine Learning Engineer. For organizations that need several specialized roles, compensation across the broader team becomes an important consideration when comparing internal hiring with an AI consulting team.

The bigger budgeting question is what capabilities you’re actually buying. If one specialized hire fills a long-term gap on an established team, hiring may make sense. If achieving the desired outcome requires several disciplines working together, leaders will want to compare the broader cost and operating requirements of building that team internally with engaging an AI consulting team. 

AI Talent or AI Consulting? Ask These Questions First 

Before choosing a model, get specific about what you’re trying to accomplish. 

1. What outcome are we working toward? 
Determine whether you’re filling an ongoing capability gap or tackling a defined initiative with specific deliverables. 

2. What expertise do we already have? 
Look across data, engineering, product, governance, security, change management, and the business itself. Understanding your existing strengths makes the gaps easier to identify. 

3. How many different capabilities does the work require? 
One missing specialty could point toward an individual hire. An initiative requiring several interdependent skill sets may benefit from a consulting team. 

4. How long will we need this expertise? 
Consider who needs to own, support, and evolve the work after the initial implementation. 

5. Who will lead the work internally? 
Even exceptional AI talent needs clear priorities, decision-making authority, and connections to the business. 

6. How will we define success? 
Agree on the business outcome, ownership, and expectations before deciding how the team should be structured. 

Workforce leadership should be part of these conversations as well. IBM’s September 2026 research found that 46% of organizations surveyed don’t involve the CHRO when AI strategy is defined.

Sometimes You Need Both AI Talent and Consulting 

For many organizations, this doesn’t have to be an either-or decision. 

A consulting team can help execute a defined AI initiative while internal talent builds the capabilities needed to support and evolve that work over time. Another company may already have experienced AI leadership and need a few hard-to-find specialists to round out its internal team. 

The right model comes back to the business objective, the capabilities required to achieve it, and which expertise the company needs to own for the long term. 

Insight Global operates across that entire conversation as a talent, consulting, and AI company. Whether your organization needs specialized AI professionals or a consulting team built around a complex technology initiative, start the conversation with us.