Generative AI (Artificial intelligence technologies that can generate new content e.g., OpenAI’s ChatGPT) has the potential to unlock once-in-a-generation efficiency gains for enterprises across all industries, but traditional IT outsourcing contracts (e.g. software development, application support and maintenance) do not yet account for these gains. As enterprise decision-makers become increasingly aware of GenAI’s potential, there is a growing call to renegotiate IT outsourcing contracts.
This article guides enterprise decision-makers to assess the value at stake from existing IT outsourcing contracts considering productivity gains offered by GenAI. Furthermore, the article also provides guidance for MSPs on how to best support enterprises to fill GenAI capability gaps while rapidly gaining market experience and recognition.
On average, enterprises spend 21% of their IT budgets on outsourcing, with contracts typically lasting between five and seven years. The baked-in year-on-year productivity gains are typically capped at between 5 and 10%, but unexpected productivity increases brought about by disruptive technology, such as GenAI, are not factored in. Enterprises are now calling for change, with a recent BCG survey finding that ~80% of enterprise IT buyers (see exhibit below) expect to use a new commercial model with the advent of GenAI.
Growing need for revamped outsourcing and commercial models due to advent of GenAI
Having been a key component in enterprise outsourcing activities since the early 1990s, MSPs now need to navigate GenAI disruption effectively if they are to remain partners of choice. Enterprises have already begun exploring GenAI capabilities, and forward-looking MSPs must now swiftly adapt to equip their enterprise customers with the solutions they need.
GenAI set to boost entire Software Development Life Cycle (SDLC)
The foundations of a typical IT outsourcing contract are made up of three key building blocks, including quality, cost, and innovation. GenAI significantly impacts all three (see exhibit below):
1. Quality: GenAI enables significant efficiency increases in support functions through chatbots, troubleshooting, and ticket routing. The impact of this technology can also be seen across the SDLC, particularly in terms of code documentation, test case generation, test execution, and improved code structuring. These use cases significantly reduce the need for reworking, and as a result, the SLAs in existing contracts should be updated or in many cases, altogether removed. Eventually, GenAI will reduce the heavy dependency on review structures between junior and senior developers, enabling junior developers to achieve quality outcomes independently.
2. Cost: GenAI has several concrete use cases across the SDLC e.g. prompt-based fast code structuring, assisted code refactoring, code documentation generation, test case generation and execution, as well as code optimisation. These use cases promise major increases in overall productivity, leading to significant improvements in cost control. Since GenAI will reduce the dependency on review structures between junior and senior developers, ultimately pyramid structures will be impacted as GenAI will (to an extent) provide code structure and quality assurance mechanisms.
3. Innovation: GenAI can automate many generic and time-consuming tasks that have typically been outsourced. The result of this is an increased capacity for developers to engage in innovation, which is set to be a vital competitive advantage as others race to adopt GenAI. Additionally, increased efficiency levels will finally enable what enterprises typically delay and avoid, refactoring and re-platforming.
Gen AI has use cases across the SDLC, impacting all three building blocks of IT outsourcing contracts: quality, cost and innovation
Nevertheless, although GenAI is rapidly evolving and being adopted, there are challenges that enterprises must be aware of in their quest to improve productivity and unlock value. BCG’s practical experiences and learnings highlight that beyond developers and other tech professionals’ adoption, the biggest obstacle in this quest can be technology itself e.g. limited traceability and irreproducibility of GenAI outcomes. A carefully crafted approach will be required when starting to implement GenAI use cases.
How to approach renegotiations if you use MSP services
Given the positive impact of GenAI across the IT value chain, it is crucial that CTOs and IT buyers understand the value at stake and evaluate the potential options for renegotiation of existing contracts. As MSPs deploy GenAI to reduce their costs, enterprises should seek a share in these savings. When doing this, enterprises should carry out a feasibility assessment (see exhibit below) with expected outcomes in mind from the outset.
Organizations should undertake a feasibility assessment and form a POV on expected outcomes before starting discussions with outsourcing partners
There are four main factors to consider when conducting such a feasibility assessment:
- The Status Quo: Before planning to renegotiate a contract, it is critical to understand whether the initial investment is significant and yet to amortize. Enterprises should also check whether a contract is in its end phase, as this could be an advantageous moment to renegotiate, as MSPs typically seek extensions. Innovation clauses (if applicable) must be assessed to understand how these translate into value towards enterprises. Finally, exit clauses must be considered, especially on account of potentially unforeseen parity or productivity increases.
- Financial Viability: Undertaking a top-down cost comparison analysis is essential for understanding the financial value at stake. For example, such a financial evaluation can consider a scenario to insource the activities if MSPs do not pass through productivity gains. Insourcing will have an initial higher cost base, but direct absorption of GenAI productivity gains can rapidly net off the cost difference against fixed year-on-year outsourcing fees. These gains can range between ranging from 15 to 30% depending on several parameters that should be considered in financial analysis e.g. number of developers, level of insourced developer, and productivity gains in existing contracts to name a few
- Strategic Alignment: Outsourcing decisions are driven by fundamental strategic business choices. Assessing the feasibility should therefore include asking fundamental questions to identify instances where outsourcing should be continued, or where insourcing should take over — e.g. Are there mature, concrete use-cases for GenAI within the IT function? Do third parties offer these services at a lower price? Will insourcing help me develop internal skills relating to GenAI? Will the technology department own the function if we start building internal GenAI IP?
- Risk and (Cyber)security: While it is easy to be blinded by the huge opportunities presented by GenAI, it is also offering new attack surfaces for increasingly sophisticated malicious actors. Because of this, IT leaders must assess whether ample risk mitigation, security measures and shared responsibilities are in place.
What if costs are non-negotiable in existing contracts?
Traditional contracts do not always allow for cost renegotiations. In these cases, enterprises can pull on the quality and innovation levers. With most IT outsourcers now building GenAI capabilities—both internally to improve cost structures and externally to tap into revenues, it is worth becoming familiar with the go-to-market (GTM) propositions that could potentially be offered as part of existing engagements (See exhibit below).
IT outsources are already investing and testing the market with GenAI capabilities
Enterprises can approach MSPs to propose the use of GenAI to increase the quality of delivery, which can ultimately be linked to existing SLAs. It is also worth enquiring about mechanisms to redeploy freed-up developer capacity to more value-adding tasks such as product development that will lead to innovation gains. To drive concrete efforts from service providers, enterprises can consider blending innovation investment commitment clauses and translating these into concrete provider commitments. For example, investing 1% of the contract value in GenAI use-cases implementation to concrete drive efforts.
How proactive MSPs can accelerate their AI journeys
Although enterprises are exhibiting a strong appetite for GenAI, BCG’s IT Buyer’s Survey revealed that lack of specific GenAI knowledge and capability is posing delivery challenges for enterprises — opening significant opportunities for MSPs. By leveraging existing affiliations, privileged levels of data access and heightened technology capabilities to help deliver, MSPs can gain authentic, real-world validation for their cutting-edge GenAI products.
Investing in the right capabilities will be crucial if MSPs are to make the most of this opportunity focusing efforts on technological collaborations and product development. Being able to offer ground-breaking GenAI-enabled products will maximize an MSP’s ability to build on existing outsourcing relationships, and potentially prolong engagements.
Proactively (and potentially complementarily) offering GenAI-based solutions to enterprises reflects good faith and cements the groundwork in place for large-scale AI integrations in the future. These collaborations enable a thorough and strategic approach to feedback-driven product evolution, helping to ensure that offerings are not outmatched by competitors.
Major GenAI efficiency gains can be a win-win situation
Enterprises stand to gain significantly greater quality and transparency from their IT outsourcing partners by proposing GenAI deployments with existing service providers.
This must be done strategically, with risk, (cyber)-security, financial visibility, and existing contractual conditions in mind. If this is done successfully, transformational productivity gains are just waiting to be unlocked.
For MSPs, GenAI presents an opportunity to further develop valuable existing client relationships by becoming an enabler of innovation.
This collaboration opens doors for longer engagements, real-world credentials, and the opportunity to be the market leader when it comes to cutting-edge products.
About the Authors
Assaf Tayar is Managing Director in the Brussels office of Platinion. His major tasks consist of the development of Platinion WESA by positioning high skilled IT capability to fulfill the benefits of the Digital transformation of our clients.
Assaf areas of expertise are Financial institutions, IT transformation with a focus of legacy modernization and Information management.
Jean-Marc Boxus is a FSI Technology leader with a keen eye on FSI impacting technologies. His 24 years professional journey is articulated around 4 building blocks: 24 years of Technology project delivery and consulting, 13 years in Application Development mainly in Financial Services (Securities processing, Insurance, private banking), 5 years managing offshoring and outsourcing delivery capabilities (Accenture), 4 years exploring business use cases around technology innovation (Cloud, Robotics, Blockchain, Artificial Intelligence)
Anas is a BCG Platinion Associate Director. Prior joining BCG, he worked as an engineer at Total then switched to consulting at companies like Timspirit and EY. He obtained both his Master’s in Electric and IT Engineering and his MBA in IT management in France. He had the opportunity to work and lead several international programs mainly within IG and FI
Sankalp is an expert in delivering large-scale digital transformation projects (including core system transformation) program management and program de-risking. He has previously worked as a Business and Technology Consultant with a focus on ERP applications consulting that covered design, implementation, lifecycle maintenance and country adoption in large-scale rollout projects.
Mayank is a Consultant in BCG’s PIPE (Principal Investor; Private Equity) team. His primary focus is performing product and technology due diligence for software companies. He has previously worked in the technology strategy team at Deloitte Netherlands, focusing primarily IT strategy and sourcing engagements. Mayank has experience in – Technology carve outs, Business analysis, IT strategy and transformation and IT sourcing strategy. He has also worked at the National stock Exchange of India where he was a part of the Futures and Options team focusing on modernizing the core order matching engine.
