All companies investing in Artificial Intelligence (AI) are at a critical juncture. AI is a growing field with unprecedented opportunities for success, but there is also a serious skills shortage.
Tech talent in the US and Western Europe is either unaffordable or unavailable.
AI offshoring is a popular solution for small- and medium-sized businesses that need the tech without the stress and extreme costs. Offshoring AI roles works, but as with any offshoring arrangement, it comes with its own set of risks.
This article thoroughly describes these risks and explains how to minimize them.
1. Data Security and Privacy Risks
AI projects often involve access to sensitive company data, including customer information, proprietary algorithms, and other intellectual property. Offshoring AI development to another country means sharing this data across borders, raising concerns about data security and privacy. There are concerns about the legalities underlying cross-border data sharing because certain countries have stringent laws surrounding these issues, and in countries where data protection laws may not be as strict as in the U.S. or Europe, this risk is exacerbated.
Mitigation: Implementing strong encryption protocols, data anonymization techniques, and secure communication channels is the best method to secure all shared data. Ensure offshore vendors comply with global data protection regulations like GDPR or the CCPA. Draft thorough data protection agreements (DPAs) with offshore vendors, specifying compliance requirements.
2. Intellectual Property Theft
Intellectual property (IP) theft can be a problem when offshoring AI development to countries where IP enforcement may be weak. Companies face the real risk of having proprietary algorithms or trade secrets misused or stolen. Most offshoring providers will work hard to keep your IP safe, and regulations around sharing material relevant to your IP will be specific and strict.
Mitigation: Protect your intellectual property with legal agreements, such as non-disclosure agreements (NDAs), that outline clear penalties for IP violations. You can also consider staggering the development of sensitive project parts across multiple vendors, minimizing the risk of any single entity gaining complete access to proprietary information.
3. Quality Control Issues
AI development and integration require meticulous attention to detail. Maintaining the quality of the AI models, code, and algorithms can become more challenging when offshoring. Differences in expertise, work ethics, and quality standards between the onshore and offshore teams can lead to subpar outcomes.
When offshoring experts build teams for companies, they screen only the most qualified professionals. In the hands of a trustworthy guide, talent quality isn’t a variable. It’s an asset.
Mitigation: Establish clear quality metrics and standards from the outset. Regular code reviews, testing protocols, and performance audits should be implemented. Companies should consistently communicate with offshore teams to provide guidance and feedback throughout development.
4. Time Zone Barriers
Offshoring AI projects involves working with teams in different time zones, and work can often be delayed. Deadlines can be missed, which can also lead to delays in communication and project updates. Miscommunication and misunderstandings between the onshore and offshore teams due to language and cultural differences can also slow progress and be frustrating.
Mitigation: Collaborate on communication platforms like Slack, Microsoft Teams, or Trello. Schedule overlapping working hours for real-time collaboration, and consider appointing a project manager who can bridge the gap between teams. Clear communication protocols, such as weekly or daily check-ins, should keep all parties aligned.
5. Cultural Differences
People in the same neighborhood often differ, so people on different continents can’t be expected to be peas in a pod. Cultural differences between onshore and offshore teams are real. These differences may include varying attitudes toward deadlines, communication styles, and problem-solving approaches. Misalignment in these areas can lead to delays and misunderstandings.
However, providers are experienced in selecting people culturally aligned with their onshore collaborators. This is one of the prerequisites of successful offshoring.
Mitigation: Even though the provider is tasked with easing this issue, be proactive about building a collaborative work culture that respects and understands cultural differences. Cultural training for both onshore and offshore teams can create comfortable working conditions and streamline communication and expectations. Video calls and team-building activities can also help.
6. Compliance with Local Laws and Regulations
Companies don’t always understand the regulatory landscape of offshore countries, which have different labor, intellectual property, and tax laws. Non-compliance with these laws can result in fines, legal disputes, and even contract termination.
Guides are naturally expected to have a good grasp of the local laws and regulations in different places. Yet, this is one of the biggest risks associated with offshoring AI roles because of the importance of remaining compliant.
Mitigation: You can consider working closely with legal experts who understand the laws in the offshore country. Ensure that contracts explicitly outline the legal obligations of both parties and include clauses that account for compliance with local regulations. Most offshoring providers also offer Employers of Record (EOR) services that can manage payroll and compliance issues on your behalf.
7. The Reliability and Trustworthiness of Offshoring Experts
Without firsthand oversight, gauging an offshoring service provider’s reliability and commitment to deadlines can be difficult. Make sure you choose a guide with proper hiring and team management experience.
This is an important bridge to cross, and it shouldn’t be taken lightly.
Mitigation: Conduct thorough due diligence before selecting an offshoring guide. Check client references, case studies, and online reviews to verify their reputation. Use smaller initial projects or proof-of-concept agreements to test their reliability before committing to long-term partnerships. Building a trusted relationship with offshore vendors is essential for ensuring smooth operations.
8. Hidden Costs
Offshoring AI development is cost-effective, but hidden costs can creep in.
Some offshoring experts can change exorbitant prices for add-on services like EOR and payroll management. These costs might even include travel expenses for in-person meetings, additional time spent on training, and managing differences in work quality. Other hidden costs include those related to longer delivery timelines due to communication barriers or rework caused by misunderstandings.
Mitigation: Offshore with experts whose bills don’t seem unreasonable or inflated. (InCommon, for instance, has a super-flexible monthly payment plan and a nominal fee for add-on services.) Develop a detailed budget that accounts for potential hidden costs, such as travel, time zone management, and extra training and quality control resources.
In any case, you should begin with a thorough cost-benefit analysis to ensure the offshoring initiative is cost-effective in the long run.
Conclusion
All the risks associated with offshoring AI development are easy to recognize and deal with.
However, businesses need to be proactive, whether by being more aware of data security concerns or knowing how to maintain/regulate the quality of work delivered. They must identify potential pitfalls and implement strategies to mitigate them.
Easier said than done? Absolutely, and that is why InCommon is here to help. InCommon carefully selects the best offshore AI talent for your team while establishing clear communication protocols, protecting intellectual property, and investing in secure, scalable infrastructures. With InCommon, risk management becomes more manageable because being transparent about the risks that lay ahead and mindful about how to overcome them is something that the team is responsible for.
As long as businesses are conscious of the risks, measures to handle them will be taken, and the benefits of offshoring AI development will continue to outweigh these challenges.
