AI has ceased to be an existential threat. Now that the “human domination” narrative has died out, it’s time to reassess our position regarding the most important technological advancement of the 21st century.
AI permeates every aspect of our daily lives. From the moment we start scrolling on our food delivery apps to when we Venmo the delivery agent their tip, we are being served by AI in some form or another. AI is transforming finance, healthcare, and even automobile engineering. But how, exactly?
By simplification. The immediate effect of all automation is simplified and improved processes. Result: “The global artificial intelligence market size was estimated at USD 196.63 billion in 2023 and is projected to grow at a CAGR of 36.6% from 2024 to 2030,” says GrandViewResearch’s Artificial Intelligence Market Size & Trends report. Machine learning, a subset of AI, is at the core of this boom. ML involves training algorithms to learn from data and make predictions or decisions without being explicitly programmed.
The number of job openings for AI and ML roles has increased dramatically in recent years.
In fact, by 2025, the number of AI-adjacent job roles in demand is predicted to be 97 million. However, the number of available AI professionals has not kept pace with this demand.
What is the impact of such a severe AI Talent Shortage?
The AI talent shortage has a few grim implications for businesses. It means longer hiring cycles. Companies spend months searching for qualified candidates, delaying all projects and initiatives with an AI dependence. This extended hiring process can also drive up talent costs as businesses compete for the same talent pool.
Secondly, the unavailability of AI professionals adversely impacts work. Existing AI teams tend to be overworked and often too burnt out to develop high-quality solutions. Overall, the company needs to maximize its AI potential.
AI talent shortages can also make retention difficult. If talent is in high demand, people are likely drowning in options. Mindless job hopping is a possibility. Every time a qualified colleague leaves, the company loses a knowledge resource.
Why Offshoring might be the solution to a Global AI Talent Shortage
The availability of AI experts varies by region. Some countries already have a large AI talent pool, which keeps growing. India, for instance, is predicted to harbor 1.25 million AI professionals by 2025. This is a solid number, but AI talent may be scarce in other countries.
This uneven distribution of talent can only be countered by offshoring. Relocating AI operations to a different country effectively solves this shortage. This is not only because the labor costs are lower in some talent-rich zones but also because the talent there is at par with the best professionals in the US.
Offshoring your machine learning team is the most reasonable decision for companies leveraging AI’s potential without breaking the bank.
This is why:
Access to a much larger AI talent pool
India, China, and Eastern European nations have many skilled AI and machine learning professionals. Bengaluru, Beijing, and Budapest have excellent tech institutes producing choice candidates in STEM fields, including AI and ML. Companies can simply access the level of expertise they need. This is especially valuable in regions with limited or expensive local AI talent supply.
Prevents overspending on AI talent
The cost of hiring AI professionals in the United States and Western Europe is prohibitive. There is intense competition for talent, which constantly drives salaries up. But AI talent costs are lower in countries where the cost of living isn’t that steep. Offshoring allows companies to access skilled talent at a fraction of the cost. These savings can be reinvested in research and development or marketing.
Increased flexibility
Quick expansion is a real plus point here. This flexibility is essential for companies that need to scale their AI operations rapidly to meet business demands. Additionally, offshoring often means 24/7 operations. With teams in different time zones, businesses know that work continues even when their local team is offline. Projects are completed faster, and the development process appears more agile.
However, offshoring your AI team is easier said than done. There are serious challenges to overcome here, many of which are an extension of the benefits. Coming up with an excellent offshoring strategy takes time. Communication barriers, cultural differences, and time zone disparities must be considered.
These must be thought about, but most are also quickly dealt with.
What to Remember When Building Your Offshore AI Team
Possible communication issues
This is unlikely within high-performing teams. Most tech talent in India, LATAM, or Eastern Europe is fluent in English and conversant with American and Western European culture. Besides, clear communication protocols exist in every company. Regular meetings and updates can also keep everyone on the same page. If there are slight language gaps, investing in language training for both the offshore and local teams can help bridge them.
Time zone disparities
Time zone differences are a challenge and an advantage in offshoring. While they allow round-the-clock work, they can also make real-time collaboration difficult. To manage this, most companies can schedule overlapping work hours where both the local and offshore teams are online. How you handle this will depend on the nature of your AI project. If you need more than a 5-hour time overlap between the offshore and onshore teams, consider Mexico your offshoring destination. If 24/7 work sounds more lucrative, India and China are good options.
Quality control in offshore work
The best offshoring destinations for AI roles are “the best” because of their level of skill, not costs. Quality control is critical for offshoring machine learning teams from day one. We typically conduct our first quality control procedures while shortlisting candidates. That is the best and most robust quality assurance process. Regular work reviews and feedback sessions can also help maintain high standards. AI is an evolving field, so make sure your offshore team has the freedom and resources to upskill while on the job.
Strengthen relationships with offshore teams
Mutual respect is vital to the success of this project. If the “offshore” team cannot be integrated into your regular workday, no cost savings can prevent a lack of team alignment. Teams on either side must share a commitment to achieving the project’s goals. If possible, visit the offshore team in person. It creates camaraderie, and the local team gets better visibility into the offshore team’s working environment and challenges.
Bringing it to a Close:
The AI talent shortage is an opportunity in disguise. A vast pool of unharnessed tech talent is eager to face the same professional challenges as their American and European counterparts. Offshoring is a viable solution to this problem, offering access to this incredible talent pool, savings, and flexibility.
Offshoring strategies are also important. For everyone needing clarification on the long and complex processes, InCommon is here to help. We have suitable hiring mechanisms and blueprints to build the perfect team of machine-learning experts for you. This article is a great place to start an offshoring plan, and for any further guidance, our hiring/team-building experts are just a click away!
