What if the biggest risk in outsourcing in the future isn’t the cost, but compliance?

Governments worldwide are tightening their AI regulations. Outsourcing contracts are no longer simply about cost, efficiency, and delivery. They are also about trust, risks, and compliance.

Recently, two major moves have affected outsourcing globally. First came the EU’s AI Act. This was the first comprehensive AI regulation globally. It set detailed and strict rules for how AI-based systems are to be built, tested, and used in real-life scenarios.

Then came the U.S. with its AI governance frameworks and executive orders. These were introduced to ensure that AI systems are safe, transparent, and accountable for their effects.

For decades, outsourcing processes were simple. Businesses hired a vendor, cut costs, and sped up their delivery. But this isn’t enough now, especially for companies outsourcing tasks related to IT and AI development.

The challenge is: how do you choose an outsourcing partner that can efficiently deliver results while meeting these new, complex requirements?

This is the question companies must answer today. Because tomorrow, the rules will no longer be optional.

Quick Primer on the New Rules

The EU AI Act

The EU AI Act is the first comprehensive set of regulations on AI by a major regulator, anywhere. It has classified AI applications into three major risk categories:

Prohibited

Prohibited (unacceptable risk) AI systems include applications made for

• Manipulating human behavior
• Exploiting the weaknesses of children, the elderly, or disabled people
• Real-time biometric surveillance in public spaces
• Social scoring by governments
• Predicting future criminal behavior

These are banned straightaway in the EU. People can neither market nor use them.

High-Risk

High-risk applications are often used in healthcare (diagnostics), or HR, such as medical devices, biometric ID, credit scoring, recruitment tools, etc. They are subject to heavy obligations based on factors like-

• Risk assessment
• Proving compliance
• Transparency
• Audits
• Human oversight
• Technical documentation
• Logging and record keeping

Businesses can develop and use such systems, but only under strict conditions.

Minimal Risk

Minimal risk AI systems include spam filters, AI-based video games, chatbots, customer support, etc. They do not have any strict legal obligations. The regulations encourage such systems and their providers to follow voluntary codes of conduct, such as transparency, ethics, etc.

Companies can develop and use such systems freely.

The U.S. AI Rules

Besides the EU, the U.S. has introduced a set of orders and frameworks at the state and federal levels. They focus on AI safety, transparency, and accountability. These include:

• Promoting trustworthy AI
• Encouraging open-source and open-weight AI
• Ensuring the protection of free speech and American values

While the EU's approach is strict and rigid, the U.S.’s approach is more flexible and driven by principles. It doesn’t have a single specific AI law, but it relies on a patchwork of state laws and federal guidance.

Federal level (Executive orders & frameworks)

1. Executive Order on Safe, Secure, and Trustworthy AI (Oct 2023)

   • First extensive U.S. federal directive on AI.
   • Requires developers of powerful AI models to share safety test results with the government (via NIST).
   • Focus on AI safety, national security, and worker rights.
   • Promote responsible AI in healthcare, education, and labor.

2. NIST AI Risk Management Framework (2023)

   • A voluntary framework made for organizations.
   • Helps businesses identify, manage, and reduce AI risks (bias, explainability, robustness, etc.).
   • Not a law, but already widely used in industries and government contracts.

3. Sector-Specific Guidance

   • Healthcare : FDA drafts on AI in medical devices.
   • Finance : SEC & Federal Reserve exploring AI use in trading and lending.
   • Defense : DoD AI ethical principles.

State-Level Rules

Some U.S. states are filling the gap with their own AI/algorithm laws:

• New York City (2023): Local Law 144 requires audits of AI hiring tools for bias.
• California : Considering broader AI accountability and transparency rules.
• Illinois : Law regulating AI in video job interviews.

Why This Matters for Outsourcing Contracts

Outsourcing contracts have gone beyond mere cost and delivery timelines. Today, they must address important compliance and accountability, especially when AI systems are involved:

• Who manages AI risk? Vendors must showcase robust risk management frameworks, including regular audits and compliance checks.
• Who explains AI decisions? Clear documentation and transparency mechanisms are essential to ensure AI decisions can be understood and justified.
• Who takes responsibility if things go wrong? Contracts should describe liability and accountability terms, specifying the roles and responsibilities of each party in case of AI-related issues.

This shift is already visible in well-regulated industries.

• A bank outsourcing fraud detection can’t just look for speed. It must demand proof that algorithms meet “high-risk” AI standards under the EU Act.
• An insurance firm outsourcing claims analysis must ensure its partner logs decisions, maintains documentation, and is ready for audits.
• A hospital outsourcing diagnostic tools must know that its vendor complies with strict healthcare AI obligations.

In short, contracts are evolving from a handshake on delivery to a safety net against regulatory fallout.

This is where providers with experience in compliance-heavy domains have an edge.

For instance, consider a U.S.-based e-logistics company that outsourced its accounts payable processes to Outsource2india. By leveraging O2I's services, the company achieved:

• Improved cash flow through the timely processing of transaction documents, including invoices and proof of delivery.
• Cost savings by reducing operational expenses associated with in-house processing.
• Enhanced efficiency by utilizing time zone differences to process transactions promptly.

This case shows the importance of selecting the right outsourcing partners that:

• offer operational efficiency,
• adhere to stringent compliance standards,
• and be accountable, especially when AI systems are integrated into financial processes.

How Outsourcing Business Models Will Shift

Older outsourcing business models focused on low-cost delivery. The newer models will emphasize compliance-driven partnerships. Vendors who embed governance, risk control, audits, and compliance will move ahead. Contracts will grow longer, more complex, and more expensive.

This shift mirrors the changes seen after the introduction of GDPR.

Here’s a simple comparison:

Aspect	GDPR	EU AI Act	U.S. AI Rules
What it regulates	Data privacy	AI systems	AI practices
Approach	Rights-based	Risk-based	Principle-based
Penalties	Up to 4% of turnover	Up to 7% of turnover	No direct fines yet
Impact	Global privacy benchmark	Likely global AI benchmark	Flexible, U.S.-driven

The Challenges Ahead

The new AI regulations promise safety and trust. But they also bring new hurdles for outsourcing partners, such as:

• Compliance costs : Vendors will need audits, certifications, and new processes.
• Regulation fragmentation : Different regions have different rules, creating complexity.
• Innovation risk : Strict rules may slow small projects or experimentation.

The positive side is that trust becomes a competitive edge. Clients will increasingly prefer vendors who can show compliance, not just speed.

The Future: A Global Standard?

Will the EU AI Act and the U.S. AI rules become the GDPR of AI? Many think so. Clients may demand a single global standard, even if laws differ by region. In the future, contracts might include AI compliance certifications, like ISO or GDPR compliance.

According to NASSCOM, India’s technology services industry is poised for a deep transformation with AI. More than USD 250 billion in tech services is expected to adapt to AI workflows.

NASSCOM also notes that the AI market is projected to grow from $110-130 billion in 2023 to $320-380 billion by 2027 (CAGR ~25–35%).

Gartner’s AI TRiSM (Trust, Risk, Security Management) framework is emerging as a global standard to manage AI risk. This includes factors ranging from governance and runtime enforcement to data handling and infrastructure.

This is exactly what model vendors will need to meet client demands in the AI regulation era.

Conclusion

As AI regulations reshape the outsourcing landscape, partnering with a trusted, compliant vendor is more crucial than ever.

For over two decades, outsourcing partners like Outsource2india have helped clients with regulated services. Be it finance back office, insurance support, or other compliance-heavy domains.

By working in domains like finance & accounting and data science, they already carry experience in regulated workflows. That foundation gives O2I a head start in adapting to AI regulation challenges. Reach out to us today to learn how we can support your business in the age of AI laws.