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.

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?

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.

In the first post in our AI & Outsourcing series, we observed how artificial intelligence (AI) is transforming the outsourcing industry in ways that extend far beyond operational efficiency. This second post in the series discusses the need to rethink legal and commercial terms that govern outsourcing relationships, as companies increasingly incorporate AI-enabled tools and automation into outsourced services.

Welcome to the first blog in our AI and Outsourcing series, where we explore the disruptive and transformative impact of artificial intelligence (AI) on outsourcing and managed services transactions.

Two years ago, many technology agreements addressed artificial intelligence (AI), if at all, through a generic disclaimer or a brief acknowledgment that AI features might be included in the offering. Today, that approach is inadequate. The integration of AI into commercial products, outsourcing arrangements, and enterprise software agreements has forced a rethinking of longstanding contract frameworks.

With the pace of new product releases and market buzz, artificial intelligence (AI) has crossed a line in many organizations from an experimental tool to an embedded business function. Companies are increasingly relying on third-party AI offerings to support core processes, streamline operations, automate customer support, and perform other back-office and customer-facing tasks.