Thinking of outsourcing your AI development project to offshore workers to reduce operational costs and maximize productivity?
You’ve come to the right place.
Running and managing the AI development project in-house can be expensive and challenging for any business, especially those that don’t really specialize in AI projects in the first place.
Hiring in-house AI software developers, data scientists, and other experts can be expensive and time-consuming, and not to mention, you may not be able to attract the right talents.
This is where building an offshore team for your AI project may be a more viable option, and in this guide, we will learn how.
Building an Offshore AI Development Team: Pros and Cons
Is building an offshore team the right choice for you? Or should you stick with your in-house team instead? Are there any other options you should consider?
Below, let’s discuss the pros and cons of building an offshore AI development team:
Benefits:
1. Cost-efficiency
This one is pretty obvious: outsourcing your AI development tasks to offshore workers will naturally save you some money on overhead expenses, especially regarding benefits and compensations.
By outsourcing the work to offshore workers located in countries with lower labor costs (and lower costs of living), we can save a substantial amount of money, and if you choose the right vendor of outsourced workers, you won’t sacrifice quality.
Oworkers offer very low-cost data entry services for only up to $4 (USD) per hour without sacrificing quality.
2. Access to a wider pool of talents from all around the world
Interviewing, hiring, and training new talents, as we know, can be very challenging and time-consuming, so if your turnover rate is high, you’ll waste a lot of money, resources, and time. On the other hand, finding the right talents that are the right fit for your AI development team can also be easier said than done.
With that being said, outsourcing to an experienced company like Oworkers can let you gain access to experienced and qualified AI development talents, including those outside your geographic location. A bigger pool of talent will ultimately translate into a better likelihood of building your perfect AI development team.
3. Faster turnaround time
Since we are outsourcing to offshore workers that are focused solely on their responsibilities, we can expect a faster turnaround time for each task.
Hiring offshore workers from different time zones can also offer some unique benefits: for instance, you can ask them to finish urgent tasks before the next business day on your location begins, so you can technically save a lot of time.
4. Allowing in-house employees to focus on core activities
This benefit is especially true if AI development is not your core business activity (i.e., if you are a software development company expanding to AI development. )
In such cases, forcing your existing in-house team to handle the AI development jobs may end up being counterproductive since they are using their time and resources not on the tasks in which they can offer their best contributions.
By outsourcing the AI development tasks to offshore experts, you can ensure your in-house employees focus their time and efforts on tasks that can contribute more to your business’s objectives, effectively improving their productivity.
Drawbacks:
Despite the benefits we’ve shared above, there are also some drawbacks to consider when outsourcing the AI development project to an offshore team. Below we will discuss some of the most prominent ones, and the potential solution for each:
1. Data security and privacy
When outsourcing your AI development processes (or any business processes at all), then you will be required to share your business’s data with the offshore workers or outsourcing vendors.
The thing is, if any of this data is confidential or regulated, then you are essentially exposing this data to various risks. Even if the offshore workers are not malicious, they may not have adequate infrastructure and/or best practices to protect your sensitive data.
Solution: it’s crucial to choose a credible outsourcing provider that has an adequate security infrastructure and maintains strict policies regarding data security. Also, evaluate whether the outsourcing vendor has non-disclosure agreements with their workers in writing.
2. Time zone differences
While, as discussed, time zone differences do have their benefits, they can also cause various challenges. For instance, your offshore workers may not be able to join important meetings during your normal business hours, and delayed responses due to time zone differences are also relatively common.
Solution: ask clearly whether the offshore workers can work at least half your business hours, and also check whether the outsourcing service provider offers 24/7 customer support to prevent delayed support during emergencies.
3. Cultural barriers
Not only your offshore workers may not speak your language (fluently), but there may also be potential cultural differences you’ll need to deal with when working with offshore workers.
Solution: make sure to choose offshore workers (or an outsourcing service provider) that have experience with clients from your geographical location and are familiar with your language/culture.
4. Focus
A common issue in outsourcing is that your offshore workers may also work with other clients in parallel, so they may not provide an adequate undivided focus for your AI development tasks.
Solution: it’s crucial to establish KPIs and a standard of quality for your AI development project before committing to an outsourcing vendor. Make sure you can measure your offshore worker’s performance accurately, and communicate your requirements before committing to a vendor.
Important Roles in an AI Software Development Team
In order to successfully establish an offshore team for your AI development project, we have to first understand the key roles required in a typical AI software development team, as well as the common requirements for each role:
1. AI Software Developer
A software developer uses their skills and experiences to write, modify, and debug software applications (in this case, AI applications) for end-user use. AI software developers are involved in the full cycle of software development from research, actual development, testing, and launch.
Requirements: degrees in software engineering or computer science, experience in developing AI software applications.
2. AI Software Engineer
In an AI software development cycle, a software engineer is responsible for leveraging data science work while applying engineering principles to create an AI application that can serve either external customers or internal stakeholders.
Requirements: degrees in software engineering or computer science, experience in data science and AI software developments.
3. Data Scientist
A crucial role in AI application developments, arguably the most important role in the whole team.
A data scientist is responsible for identifying, collecting, and processing a company’s data for use in AI applications. The data scientist identifies the data an AI application needs to meet its goals. The required data can be generated internally or gathered from external sources.
The data scientist must identify whether the data is appropriate for the application (i.e., whether the data is out of date or there isn’t enough data) and process the collection of data accordingly.
Requirements: degrees in computer science, math, statistics, or economics. Competent with machine learning and statistics. Experience in data management software.
4. Project Managers
You can either stick with your in-house project manager (if any) or outsource the role to an offshore worker.
In an AI development project, a project manager’s role is to oversee and manage the whole project to ensure the project stays within the agreed budget and timeline. The project manager is accountable for the entire project scope, including the project budget.
Requirements: degrees in business or computer science, Project Management Professional (PMP) certification is a plus. Proven competence in project management.
5. UX Designer
A User Experience (UX) designer is responsible for creating compelling and satisfying experiences for end-users when using the AI application developed in the project.
It’s crucial to consider that many AI applications involve interactions via voice (i.e., Alexa), which may require a specific approach to UX design.
Requirements: degrees in graphic design or other relevant fields, demonstrated experience in creating and implementing UX designs, competence with design programs (i.e., Adobe Photoshop).
6. Subject Matter Experts
A subject matter expert (SME) offers highly specialized knowledge regarding a specific practice, process, piece of equipment, or other areas.
In AI development, subject matter experts of the field covered by the AI application can play an important quality assurance role, determining whether the output of the AI model matches the desired result or whether further adjustments by the data scientists are needed.
SMEs are typically outsourced, and you may need different SMEs for different AI development projects depending on the intended implementation of the AI model.
Requirements: 10-15 years of experience working in the area of expertise. Knowledge in project management and business operations.
Key Considerations When Choosing an Outsourcing Service Provider
So, you’ve finally made up your mind about building an offshore team for your AI development project?
Then, the next step is to choose the right outsourcing service provider capable of delivering the offshore workers to run your project.
As you can see from the challenges we’ve discussed above, choosing the right outsourcing vendor is crucial if you want to achieve success in your AI development team, and below are four main considerations you should have when choosing between different outsourcing vendors:
1. Know your needs and requirements
Your business is unique, and your AI development project is also unique. So, you’ll have unique needs and requirements in offshore workers, and the key in choosing the right outsourcing vendor is to first identify what these unique needs are.
Make sure to clearly map your business’s AI development requirements before evaluating and committing to an offshore outsourcing vendor. For example, will your project need a Subject Matter Expert (SME) on a specific subject? If the answer is yes, then you might want to look for an outsourcing provider capable of bringing you this specific SME role.
2. Evaluate knowledge and experience on AI field
The AI field, as we know, is relatively young. Not all outsourcing service providers may have adequate experience and expertise to ensure accuracy and quality to fulfill your AI project’s requirements. When checking between different
Oworkers has handled various projects including AI developments since 2013 and can manage data outsourcing operations in more than 20 languages with previous clients including Xerox, Walmart, and PWC, among others.
3. Reputation
Fortunately, nowadays we can easily research the credibility and reputation of any outsourcing vendors online.
So, use this to your advantage: make sure to perform thorough research on the outsourcing vendor you are planning to partner with by checking online reviews and client testimonials.
In fact, if the said company doesn’t have any reviews or testimonials from previous clients, it’s a clear red flag. If possible, contact their previous clients to confirm their claims.
You should also make sure that the data entry outsourcing provider is financially stable so you can ensure they can stay up-to-date with the required resources and infrastructure.
4. Cost
Pretty self-explanatory, will the outsourcing provider’s pricing fit your budget? However, you shouldn’t always go for the most affordable option so that you are sacrificing quality of work.
Remember that the main objective of outsourcing your AI project to offshore workers should be about improving cost-efficiency. So, calculate thoroughly how much the outsourcing service can reduce your operational expenses.
Wrapping Up
As you can see, the benefits of building an offshore team to handle your AI projects far outweigh the cons. While there are indeed some concerns to be had before signing off with an outsourcing service provider, all of them are manageable and can be resolved by choosing an established data entry service provider with enough experience in AI projects.
Oworkers is an established offshore outsourcing solution with professional, well-trained AI experts guaranteeing high-quality results and consistency of service for your AI development projects.
