We are a flexible workforce solutions provider to Series B funded startups, VC and PE firms, SaaS, brands, agencies, and Fortune 50 companies.

Cost-effective AI Talent Hiring Strategies for SMBs

AI Hiring Strategies - Chess Pieces

For small and mid-sized businesses, artificial intelligence (AI) stands out as a beacon of transformative potential, especially for those seeking to carve out a competitive edge and future proof their business. However, the journey towards AI integration is fraught with decisions that can significantly impact the delicate balance sheet of these organizations. This is often seen when looking to hire AI talent.

This leaves SMBs to confront two pivotal questions: First, how do we best integrate AI into our product and service offering without exhausting our resources? Second, what AI hiring strategy is going to be most cost-effective?

Here we dissect the three most common AI hiring strategies: cultivating an in-house team of AI specialists, employing the surgical precision of freelancers for targeted projects, or engaging with consulting firms for an all-encompassing solution. Each strategy is weighed against the backdrop of cost implications, scalability, depth of expertise, and the nuanced demands of project management.

We aim to equip SMB owners and decision-makers with the knowledge to make informed choices that align with their business goals, resources, and long-term vision for AI integration, ultimately demystifying the journey towards becoming more competitive through AI technology. To read the executive summary and view a visual table breaking down each AI hiring strategy, scroll down to the bottom on the page.

Option 1: Hiring In-house AI Experts

In determining whether it makes sense to hire in-house AI experts, you need to first determine whether it fits into your talent strategy. This involves looking holistically across departments to see what talent gaps currently exist relative to your organization’s strategic priorities and budget. However, only 38% of companies have a documented talent strategy through which they can reference, while a mere 12% align that strategy with their business strategy.

If talent gaps exist – meaning you do not have talent with the skills, experience, and technological expertise needed for a given role – it’s time to consider hiring new talent. Common roles to consider hiring for include AI Project Managers, Machine Learning Engineers, and Data Scientists.

The benefits:

Dedicated focus: The biggest benefit hiring full-time AI experts is their ability to provide dedicated focus on your AI initiatives. Unlike contractors or fractional experts, these employees do not split their time, energy, and resources across a variety of projects and are able to fully immerse themselves in understand your specific AI challenges, application goals, and launch cycles.

Accelerated Innovation: Another significant benefit of nurturing an in-house team is the acceleration of AI-driven innovation. AI Project Managers and Systems Architects have the advantage of immediacy when it comes to acting on insights or iterating on projects. There’s a certain agility that comes from being on the ground, able to make quick decisions and pivot strategies in real-time based on the company’s performance, market shifts, and customer feedback. Furthermore, the ongoing relationship between AI developers and business stakeholders within the company can lead to a more “organic development” of tools and systems that are not only cutting-edge but are also closely aligned with the strategic business objectives.

Team synergy: Imagine the harmonious interplay between AI Software Developers and other departments, creating solutions and tackling challenges as they arise. Data Analysts within arm’s reach of your core teams can translate into dynamic exchanges of insights, fostering an environment where agile AI development is not just a goal but a reality.

Intellectual property: Having AI Researchers under your roof can secure the lifeblood of your competitive stance in the market. Moreover, the long-term accumulation of expertise, particularly from specialized roles like AI Specialists, ensures that the knowledge stays within the company walls, reducing external dependencies.

Integration & Efficiencies: Perhaps the most important benefit, however, is the integration possibilities that comes with in-house expertise. Ultimately, deeper customization and more seamless integration of AI technologies with existing IT infrastructures can be created with less friction. This leads to a more cohesive ecosystem that supports efficient operations.

The drawbacks:

However, the decision to hire in-house doesn’t come without its drawbacks.

Cost & Competition: The steep entry price for talent, especially for sought-after roles like Full Stack AI Developers, can be daunting. These initial costs extend beyond salaries into the realms of training and development, where the upkeep of skills, particularly for roles such as AI Research Scientists, can be both expensive and resource-intensive. Competing with large companies like JPMorgan Chase, Accenture, and Disney, all of which are actively hiring AI-talent are offering salaries ranging from $100,000 to $338,000. However, there is some good news for employers. Average pay hike for a new job in AI — including AI/ML engineer, robotics engineers, natural language processing engineer, ethics engineer and data architect — has reduced to 15-25% from 50-60% in 2023.

Scalability: A recent Gartner report predicts that more than 75% of organizations will shift from piloting AI technologies to operationalizing them by the end of 2024 — but will your existing team be able to keep up? As Manasi Vartak, CEO of Verta – an MLOps platform, says, “Getting one or two AI models into production is very different from running an entire enterprise or product on AI. And as AI is scaled, problems can (and often do) scale, too.”  So, Systems Architects might build you a robust foundation, but can they stretch it to match your growth trajectory? The risk of finding your team’s capabilities maxed out as your business evolves is a serious consideration that could only be solved by augmenting them with external options or additional full-time employees.

Underutilization: Particularly for smaller operations, the full spectrum of an AI Analyst’s skills might not be consistently in demand. Unlike larger corporations where data volumes and complexity may require constant attention from a full-time team, SMBs can find that their needs do not yet warrant a full-time AI staff. The cyclical nature of some businesses could mean there are periods when the AI team is not fully engaged, leading to inefficiencies and a drain on resources.

Project complexity: Finally, the large scope and depth of AI projects often necessitates a multidisciplinary approach that can be difficult for SMBs to support in-house. AI projects don’t just require technical prowess; they also benefit from industry expertise, regulatory knowledge, ethical considerations, and integration with existing business processes.

In sum, the decision to cultivate an in-house AI team is rife with pros and cons. SMBs must carefully balance the allure of a dedicated, synergistic team with the realities of high costs, scalability issues, and the fast-paced nature of AI innovation. The path is fraught with challenges, but for those who navigate it wisely, the rewards can be substantial, positioning their business at the forefront of AI-enabled industry leaders.

Option 2: Hiring Freelance AI-Experts

Navigating the complex waters of AI implementation, many SMBs are increasingly drawn to the allure of hiring freelance AI experts. This agile workforce option promises access to a diverse pool of talent, each with their own specialized skill sets. But what really are the benefits and drawbacks of each option?


Cost-efficiency: Operating on a tight budget? Freelancers offer a high level of expertise without the long-term financial encumbrances of full-time employees. This approach allows you to bypass the hefty recurring costs of salaries, benefits, and continuous professional development that are part and parcel of nurturing an in-house team. Instead, they can allocate resources on an as-needed basis, paying for specific AI tasks or projects, which can lead to significant cost savings while still driving forward their AI initiatives. The cost for an AI Engineer can range anywhere from $100-$250/HR, while off-shore AI Developer rates can be as low as $50-75/HR.

Flexibility: Flexibility is the cornerstone of freelance engagement. The ability to swiftly adjust the scale of your workforce in response to project flow could be invaluable, especially if you already have AI talent in-house. Freelancers enable you to react to project demands dynamically, expanding and contracting the pool of AI experts without the logistical and financial complexities of hiring or releasing full-time staff. This flexibility is not just a matter of headcount; it’s about the agility to explore new AI projects with the confidence that the workforce can adapt to evolving needs.

Access to a wider-talent pool: The freelance market is a global one, offering you an extraordinary diversity of AI talent. Whether the need is for a niche skill set for a cutting-edge AI project or for seasoned expertise in a more traditional AI application, the vast talent pool of freelancers means SMBs can pinpoint the ideal expert regardless of geographical or logistical constraints. This access breaks down barriers to innovation and allows SMBs to leverage a world of expertise that might otherwise be beyond reach. This may also facilitate leveraging AI-talent from diverse backgrounds. According to HBR, the highest concentration of AI talent still resides in San Francisco. However, other global hubs like Bangalore, Toronto, Singapore, Paris, and Melbourne offer both wide and diverse talent pools to source from.

AI Hiring Hotspots By City

The drawbacks:

However, hiring freelancers is not without its challenges. From the intricacies of project management and company alignment to concerns over intellectual property and long-term focus, the decision to hire freelancers carries weighty considerations.

Less Control and Oversight: One of the trade-offs of engaging freelancers is the reduced control over how and when work gets done. This can manifest as challenges in project coordination, oversight, and consistency in deliverables. The autonomous nature of freelancers means that you may need to develop more robust project management strategies to ensure deliverables meet their standards and timelines, which can be an additional overhead not present with in-house teams.

Limited Company Knowledge: While freelancers can be adept at diving into new projects with little lead time, they likely won’t possess any deep understanding of your unique operational context or long-term strategic goals. The lack of ingrained company knowledge and additional onboarding time can sometimes result in a misalignment between project outcomes and the broader business objectives, requiring more effort from you and your team.

IP and Security Risks: The transient nature of freelance work raises red flags for SMBs when it comes to intellectual property (IP) and data security. Sharing sensitive information with external parties inherently increases the risk of IP theft or data breaches. For SMBs, establishing robust confidentiality agreements and security protocols is crucial, but even with safeguards, the risk is higher compared to in-house teams who are consistently under the umbrella of the company’s security infrastructure.

Short-Term Focus: Freelancers are often project-driven, which means their focus may be on delivering specific outcomes rather than on the long-term success of the company. This distinction can lead to challenges in creating sustainable, scalable AI strategies that evolve with the business. The transient commitment of freelancers may necessitate a more strategic internal oversight to ensure continuity and long-term value of AI projects.

Inconsistency in Skill Levels: The freelance market is vast and varied, with professionals ranging from highly experienced and skilled experts to those who are less qualified and simply selling a false narrative. This disparity can make it challenging to consistently find freelancers who meet the quality standards required for complex AI projects. The lack of a standardized vetting process means you may encounter a trial-and-error phase before securing freelancers whose skills genuinely align with their needs.

Lack of Industry-Specific Experience: While freelancers may possess technical AI skills, they might lack specific knowledge or experience in your industry. This gap can result in solutions that are technically sound but may not fully address the unique challenges or opportunities within your sector, affecting the overall effectiveness and quality of the AI solution.

Navigating the freelance AI talent market poses distinct challenges, from ensuring project alignment and safeguarding sensitive data to finding freelancers with the right blend of skills and industry knowledge. Outsourcing to AI consulting firms can offer a structured, secure, and expert-driven solution, often streamlining the path to AI integration and innovation. Let’s explore both the benefits and the drawback that option presents.

Option 3: Hiring Outsourced Consultant Firms

As you strive to keep pace in a rapidly evolving digital landscape, the decision to employ outsourced consultant firms presents itself as a strategic pivot towards harnessing AI. This approach to AI integration uses a partnership model that connects you with a cadre of external experts with a singular firm. Outsourcing to consultant firms not only opens doors to a broader spectrum of AI expertise and capabilities, but also embeds cost-effectiveness and risk mitigation into the very fabric of the project lifecycle. However, this route is not without its complexities. As we explore the benefits and drawbacks of hiring outsourced consultant firms, it’s imperative for you to navigate this terrain with a balanced perspective, fully aware of the potential challenges that accompany the outsourced model of AI adoption.


Using outsourced consultant firms offers unique benefits unattainable with in-house resources alone. These firms bring a wealth of experience, having partnered with countless companies to tackle similar challenges, allowing them to refine strategies that fast-track success. They have tried-and-tested processes, automation, and proprietary knowledge that can accelerate project completion. Moreover, their exposure to a wide array of business outcomes arms them with insights into the anatomy of success and the pitfalls of failure. But there’s more.

Cost Predictability: Outsourced consulting firms typically have a clear cost structure associated with their services, aiding in financial planning and budget management.

Expertise and Specialization: When you partner with outsourced consultant firms, you tap into a vein of deep expertise and specialization that is hard to match. These firms are staffed by seasoned professionals who bring a wealth of knowledge across various domains of artificial intelligence. This ensures that even the most complex AI challenges are approached with the highest level of proficiency, offering SMBs the kind of expertise usually reserved for industry giants.

Scalability: The scalability offered by consulting firms can be a game-changer. These firms can allocate additional resources swiftly to ramp up for large-scale projects or scale down as projects wind down or needs change, providing a level of flexibility that is often unattainable with in-house teams. This adaptability means that you can remain agile and responsive to market demands without the fixed overheads associated with a permanent staff of AI experts.

Risk Mitigation: With their extensive experience and established protocols, these firms are adept at navigating the complexities of data security and regulatory compliance, two areas where SMBs often face vulnerabilities. By offloading these risks to the consultants, you can focus on innovation and growth, secure in the knowledge that their AI initiatives are in experienced hands.

Access to cutting-edge technology: Partnering with consultant firms enables you to gain access to cutting-edge AI technology, a privilege that can be prohibitive both financially and technically for many smaller companies. Consulting firms typically bring the latest tools and technological advancements to the table, ensuring that SMBs are not left behind in a tech-driven landscape. This access can be crucial for staying competitive and can open up new avenues for business innovation and customer engagement.

Industry Insights: The diverse industry experience that consulting firms possess can be invaluable for SMBs. Consultants who have worked across sectors bring with them a treasure trove of insights and best practices, that can be leveraged. This cross-pollination of ideas can lead to innovative solutions that may not have been conceived within the silo of a single industry.


Outsourcing AI projects to consulting firms, while beneficial in many aspects, also brings a set of drawbacks that SMBs should consider.

Reduced Control: Relying on an external firm means you may have less direct oversight and control over the minutiae of project development, potentially leading to outcomes that may not entirely align with the company’s vision.

Hidden Costs: While outsourcing can provide cost predictability, there can be hidden or unforeseen expenses, such as those arising from project scope changes or additional requirements not covered in the initial agreement.

Long-term Engagement Costs: While initially cost-effective, long-term engagement with consulting firms for ongoing AI needs can become costly over time, possibly exceeding the investment in building an in-house team.

Integration Issues: AI systems need to be finely tuned to work seamlessly with existing business processes and IT infrastructure. Consultants may develop sophisticated AI models that work well in a test environment but face compatibility issues when deployed within your unique ecosystem, which can have different data formats, legacy systems, and business rules.

Intellectual Property Concerns: Working with external firms can raise concerns about the ownership and confidentiality of intellectual property, especially if the consulting firm works with multiple clients in the same industry. As noted by authors Gil Appel, Juliana Neelbauer, and David A. Schweidel in their article Generative AI Has an Intellectual Property Problem, at minimum, “businesses should add disclosures in their vendor and customer agreements (for custom services and products delivery), if either party is using generative AI to ensure that intellectual property rights are understood and protected on both sides of the table as well as how each party will support registration of authorship and ownership of those works.”

Technology Lock-in: Outsourced firms might develop AI solutions that lock you into specific technologies or platforms, limiting future flexibility and potentially increasing long-term costs due to dependency on proprietary tools or software.

In summary, while outsourcing AI can offer short-term benefits for SMBs, it’s crucial to consider the longer-term drawbacks. Less control and potential hidden costs can impact alignment with company goals and budget. Issues with AI integration and the risk of technology lock-in could impose limits on business agility. Furthermore, safeguarding intellectual property is paramount in any external partnership.


Navigating the AI adoption landscape is no small feat for SMBs. It’s a balance of innovation and prudence, where the choices made today can define tomorrow’s success. Whether building in-house capabilities, tapping into the agility of freelancers, or leveraging the full spectrum of outsourced consulting firms, the decision on which AI hiring strategies to deploy must be aligned with your both your short and long-term business objectives. Yet, with only 38% of companies having a documented talent strategy and even fewer aligning it with business strategy, it’s evident there’s room for improvement and support.

This is where Talentfoot steps in. We offer a complimentary assessment with our technology recruiting practice, specifically tailored for your small business. It’s time to clear the fog around AI-hiring strategies and make an empowered decision. With Talentfoot, you can ensure that your AI journey is not just about keeping up but setting the pace. Take the first step towards a future-proofed business—reach out to Talentfoot for your assessment today.



For SMBs, adopting AI is a strategic move that promises significant benefits for those who navigate its complexities with foresight. But deciding on whether or hire in-house, freelancers, or a consulting firm requires you to consider several things:

  • Strategic Planning: AI implementation needs careful alignment with a well-documented talent strategy, which is currently lacking in most SMBs.
  • Hiring Options:
    • In-house teams provide dedicated focus and safeguard IP but can be expensive and less flexible.
    • Freelancers offer cost savings and adaptability but come with challenges in control and IP security.
    • Consulting firms deliver expertise and scalability, yet they can incur unexpected long-term costs and reduce project control.
  • Support and Guidance: Talentfoot’s complimentary assessment is available to help SMBs find the right AI solution that aligns with their business strategy, ensuring a considered approach to adopting AI.

AI Hiring Strategies Overview Table

Criteria In-house AI Experts Freelance AI Experts Outsourced Consultant Firms
Dedicated focus on AI initiatives
Accelerated AI-driven innovation
Team synergy within the company
Retention of intellectual property
Seamless integration with existing infrastructures
Workforce scaling flexibility
Access to global talent pool
Cost predictability
Specialized expertise and experience
Scalable resources
Risk mitigation (security/compliance)
Access to cutting-edge technology
Control over project details
Hidden costs
High long-term engagement costs
Integration issues with business processes
Intellectual property concerns
Technology lock-in risks