Generative artificial intelligence (AI) has disrupted the global market since its scaled capabilities were unveiled to the world by OpenAI at the end of 2022.
Today, most enterprises either want to adopt this game-changing technology or are looking to build their own gen AI capabilities, but at what cost? Reach out to us to discuss this topic further with our expert analysts.
Billions of dollars have now been invested into building and leveraging gen AI, with the hope that it will improve business operations with unprecedented productivity improvements.
Similarly, on the information technology (IT) services side, many service providers have begun investing in proprietary gen AI solutions to pass on the associated efficiencies to their clients, all while identifying new use cases during delivery. While the offering of gen AI-driven productivity was considered a differentiator for providers in 2023, this has become a table stake in the past two to three quarters. Despite all of this, a big question remains: “Is the providers’ proposition aligning with client expectations regarding ROI?”
In this blog, we delve deeper into the current expectations in IT outsourcing deals.
Demanding more from gen AI: enterprises raise the bar
With a varying degree of success from the proof of concepts (POCs), enterprises now expect service providers to clearly demonstrate a visible return on investment before approving fresh investments. Enterprises are now expecting clear call outs on both capabilities, as well as true efficiencies from their gen AI solutions.
In this regard, some of the leading providers have started to highlight specific details as a part of their gen AI solution value proposition, such as:
- Quantifying productivity: What are the incremental productivity gains over the deal term?
- Cost benefits: How would the improvement in productivity translate into noticeable cost benefits? This should take into consideration the reduction in the overall Total Contract Value (TCV) of IT outsourcing deals, both with and without the gen AI proposition
- Intangible benefits: How will the gen AI solution lead to an enhanced user experience? For example, highlighting potential reduction in the meantime to resolve (MTTR) or improvement in customer satisfaction (CSAT) scores
Please note that with the advent of new technologies like Agentic AI, the cost implications and the productivity benefits are also expected to increase in the future.
The gen AI return on investment (ROI) dilemma: Is it worth the hype?
Despite the allure of gen AI, executives are under increasing pressure to justify its seemingly hefty price tag. Demanding an ROI of at least 2-2.5x, they’re wary of projects that fizzle out after initial proofs of concept due to the soaring costs and its unclear benefits.
To address these concerns, enterprises are demanding greater transparency and more accountability from providers, scrutinizing costs associated with resources, infrastructure, data, and large language models (LLMs).
There are also concerns around the associated capital expenditure. In response to these demands, providers are strategically positioning gen AI as a long-term value proposition by amortizing the upfront costs over the contract period. In most cases, especially in competitive IT services opportunities, we are also observing a few leading providers proposing gen AI solutions as an investment from their side.
To safeguard the interests of both parties, contracts are now evolving to include detailed discussions on risk, regulatory compliance, commercial impact, and implementation costs. Periodic benchmarking clauses are also being negotiated to ensure ongoing accountability and prevent unforeseen expenses.
Everest Group partners with both enterprises and leading IT service providers on mandates related to pricing strategies, productivity gains, and pricing impact related to gen AI.
If you found this blog interesting, check out our virtual event, Gen AI Unhyped: How It Is Evolving and How to Plan for Success.
To discuss this topic in more detail or for a detailed analysis, contact us at [email protected], or please contact Prateek Gupta and Anubhav Jain.