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.

A teenager opens an app. The feed is personalized based on earlier activity. The next video starts automatically. A companion chatbot remembers yesterday’s conversation. To the user, these may appear to be features of one service. Under a new package of California laws, they are separate design choices that can carry different compliance 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?

Modern brand partnerships raise contract questions around exclusivity, reputational risk, how influencer and celebrity content can be used after it is posted, and how the parties will measure performance. Part 2 of this Contract Corner series examines how parties can address those issues in their agreements.

Brand partnerships are expanding beyond traditional sponsorships and celebrity endorsements into arrangements that can combine licensing, content creation, product development, distribution, and data sharing. As those relationships become more complex, contracts need to clearly define the partnership, control of brand assets, and what happens to jointly created materials when the relationship ends.

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.