Tech & Sourcing @ Morgan Lewis

A company licenses an artificial intelligence–enabled service after evaluating its functionality, security, performance, and compliance characteristics. Six months later, the provider upgrades the underlying model or replaces it altogether. The product may look the same, but the technology beneath it may have changed in ways that affect performance, data processing, regulatory compliance, or the customer’s downstream obligations.

When an M&A transaction closes, the buyer will typically be unable to stand up its own IT environment on day one. In this scenario, the seller often continues operating existing IT systems, provides access to employees who understand them, and delivers data needed for the transition for a period after closing to assist the buyer in eventually operating a standalone IT environment of its own.

As artificial intelligence (AI) becomes increasingly embedded in development services, outsourcing arrangements, and other commercial and technology transactions, customers and vendors are confronting a deceptively simple question: How should risk be allocated when a deliverable is created using AI?

Signing up for a streaming service might be faster than choosing what to watch, with only a few taps unlocking a month of movies, a season of sports, or enough airline Wi-Fi to make a long flight feel shorter. That convenience, however, rests on a recurring contract that may continue after the vacation ends, change price while it remains in effect, and provide less control over content than the word “subscription” suggests.

While a freedom-to-operate (FTO) analysis often centers on patent or trademark searches, contractual commitments can establish the practical boundaries—or maze—of a company’s degrees of freedom. Organizations with a checklist of high-level issues to be addressed during contract discussion and negotiation (such as liability, compliance, and data protection) should consider adding FTO to that list. With a more holistic perspective of the FTO landscape and with business and technical teams’ input, commercial counsel can find creative ways to complete the puzzle.

Global outsourcing transactions often require companies to navigate not only complex commercial issues, but also employment-related regulations and local practices that can vary significantly across jurisdictions. As organizations continue to transform their operations through outsourcing, managed services, and digital and AI transformation initiatives, labor and employment considerations have become an increasingly important part of transaction planning. Partner Kat Gibson advises multinational companies on the employment issues that arise in outsourcing transactions, including employee transfers, workforce restructurings, reductions in force, consultation obligations, and cross-border employment compliance. We recently sat down with Kat to discuss some key labor issues companies should be thinking about when planning global outsourcing transactions.

Flexibility versus certainty is an important and often challenging tradeoff throughout commercial contract negotiations, particularly regarding termination for convenience. Customers, mindful of shifting budgets, technological changes, and evolving business needs, want the freedom to walk away at their discretion. Vendors, mindful of upfront infrastructure investments, staffing needs, and revenue volatility, want a committed income stream. Reconciling these competing needs can become a significant sticking point, often arising later in the negotiation cycle after other issues have been settled.

Throughout this AI & Outsourcing Services series, we have explored how artificial intelligence is transforming the outsourcing industry, reshaping contract terms, creating new forms of vendor dependency, and redefining how value is measured and priced. As organizations increasingly deploy AI-enabled technologies within outsourced environments, another critical issue is emerging: governance.

The fourth blog in our AI and Outsourcing series examines another significant consequence of AI-enabled outsourcing: the fundamental shift in how parties define, measure, and price value. As artificial intelligence (AI) becomes embedded in service delivery, traditional pricing models based on labor inputs, headcount, and transaction volumes are increasingly being challenged. Customers and service providers alike are reevaluating how outsourcing arrangements should be structured when automation and AI-driven efficiencies can dramatically alter the economics of service delivery.

As artificial intelligence (AI) becomes increasingly embedded in outsourced services, companies are facing a new and growing challenge: digital dependency on their vendors. Modern outsourcing relationships are no longer limited to staffing support or standardized technology platforms.