The emergence of AI 2.0 is transforming the IT landscape, compelling organizations to reevaluate long-standing practices, including their approach to outsourcing. As AI tooling becomes more advanced and integrated into strategic operations, the traditional outsourcing model may no longer align with the evolving needs of organizations. This shift presents a critical opportunity to rethink how outsourcing fits into the broader AI 2.0 adaptation journey.

The Hidden Costs of Outsourcing

The work of Nobel laureate Oliver Williamson, particularly his research on transaction cost economics, offers valuable insights into the hidden costs of outsourcing. While outsourcing may seem financially attractive, it comes with coordination costs, contract management complexities, and risks related to vendor dependency. In the context of AI 2.0, these transaction costs may outweigh the benefits as organizations find they can consolidate IT functions internally with the help of AI tools.

When IT functions shift toward strategy and decision-making, outsourcing could become a liability rather than an asset. AI-driven platforms now automate many operational tasks, reducing reliance on external vendors while improving efficiency and scalability.

The Shift in Roles: From Operational to Strategic

Historically, organizations outsourced job functions to reduce costs and streamline operations. However, AI 2.0 is reshaping this dynamic. Taking IT organizations as an example, IT functions are evolving from operational to strategic and decision-making roles, embodying a "shift-upwards," as I describe in my book, A Quick Guide for IT Organizations: AI 2.0 Adaptation Through ITIL 4.0. Many roles will focus on quality, consistency, alignment with business objectives, and strategic decision-making rather than routine tasks.

This shift almost resembles “outsourcing to AI 2.0 tools” rather than human teams, as traditional outsourced functions like application development could be consolidated by AI platforms. Internal employees will transform into hybrid project-lead like roles—blending technical expertise with strategic oversight—enabling companies to reduce reliance on external providers and manage AI-augmented projects in-house.

Reevaluating Outsourcing as Part of AI 2.0 Change Management

Considering The Hidden Costs of Outsourcing and The Shift in Roles, reevaluating outsourcing strategies must become an integral part of the change management process to ensure that evolving job functions align with the broader strategic goals of the organization.

Tasks traditionally handled by large outsourcing teams may now be executed more efficiently in-house, augmented by AI tools. To adapt effectively, companies must avoid limiting their evaluation to the constraints of their current outsourcing model. Instead, they should assess their operations as if everything were managed internally, end-to-end. This perspective removes the "outsourcing lens" and allows for a more accurate understanding of how processes and functions can be streamlined, automated, or transformed with AI 2.0.

A structured evaluation process should focus on:

Internalization of Strategic Roles: Retaining critical functions within the organization to ensure alignment with AI-driven goals.
Transitioning Routine Tasks to AI: Leveraging AI tools to consolidate functions that required human manual involvement.
Identifying Job Function Consolidation and New Role Creation: Evaluating which roles can be consolidated or refined and defining new positions required to support AI-driven operations.
Viewing Operations Holistically: Adopting an internal-first mindset to evaluate workflows comprehensively, enabling a clearer path for AI-driven transformation.

By treating the organization as a unified entity during this evaluation process, companies can identify synergies, eliminate redundancies, and unlock the potential of AI 2.0.

Reassessing the Role of Third-Party Vendors

As organizations redefine their operations with AI 2.0, the role of external vendors must also evolve to complement this transformation. Rather than outsourcing commoditized tasks, organizations should engage third parties where an external, unbiased perspective is essential. For example:

Independent Auditing of AI Systems: Ensuring transparency and fairness in AI decision-making processes through external assessments.
Compliance and Regulatory Reviews: Providing expertise in navigating complex and evolving AI regulations, particularly in industries like healthcare, finance, and insurance.
Bias and Risk Evaluations: Conducting impartial reviews of AI models to identify hidden biases, risks, or ethical concerns that might be overlooked internally.

This approach ensures the integrity and accountability of AI initiatives while allowing internal teams to focus on strategic, high-impact activities.

The Future of Outsourcing Giants

This transformation will significantly impact traditional outsourcing providers, including industry leaders like Infosys, TCS, and Wipro. Their business models, heavily reliant on delivering outsourced IT services, may face disruption as organizations increasingly automate routine tasks and prioritize in-house expertise. These outsourcing giants will need to pivot toward offering niche services where unbiased third-party perspective is essential, to remain relevant in the AI 2.0 era.

Will they evolve to meet these new demands, or will they struggle to maintain their relevance in an AI-first world? This remains an open question—one we’ll explore in a future article.

Conclusion: Key Takeaways

Evaluate the Entire Ecosystem: Companies must look at all functions—internal and external—as part of a unified operation. Only by doing so can they determine which tasks should remain internal, which can be automated, and which require impartial, third-party involvement.
Focus on Strategic Expertise: Retain and upskill internal teams to handle strategic functions like managing AI tools, quality assurance, and aligning operations with business goals.
Leverage Third-Party Expertise Where It Adds Value: Use third-party vendors for impartial roles like auditing AI systems, assessing compliance, and conducting unbiased reviews.

The outsourcing landscape is poised for disruption, and companies must act now to ensure they stay ahead of the curve. How is your organization preparing for this shift? Let’s connect to explore how to align your outsourcing strategy with your AI 2.0 goals.

Journey to AI 2.0: Outsourcing Strategy Reform