Global business leaders are urging CIOs to implement generative AI (GenAI) at scale, in hopes that it will enhance organizational productivity and improve operating margins, especially in the face of budget constraints. Yet delivering measurable cost savings in the near term through productivity proves elusive.
The assumption is that incremental productivity gains from GenAI — faster code development, quicker report generation, swifter customer support — will translate smoothly into financial savings. Yet, despite persistent executive enthusiasm, CIOs struggle to realize meaningful bottom-line improvements from productivity-focused initiatives.
CIOs should adopt a GenAI strategy centered on financial efficiency to cut costs, save cash, reduce losses and risk, and boost near-term return on investment (ROI). Six specific tactics are detailed below. CIOs do not need to do all; they should start with the most feasible and impactful tactic for their organization and should acknowledge that this approach may reshape their GenAI strategy.
Pursue Cost Reduction Within IT
There are three tactics CIOs can use to implement a financial efficiency strategy within their own function and directly reduce the IT budget.
Outsourcing haircuts: Outsourcing constitutes over 13% of the average IT budget, presenting CIOs with opportunities to renegotiate contracts using GenAI.
Although vendors face challenges in realizing productivity savings, competitive pressures drive outsourcers to offer 5%-20% price reductions, often mid-contract. To capitalize on this, CIOs should benchmark current supplier agreements, engage new suppliers for competitive pricing, and renegotiate or switch providers to achieve significant savings.
Reducing third-party variable spend: CIOs often use small, variable contracts with external specialists. CIOs have successfully cut costs by encouraging their staff to use GenAI for tasks typically handled by contractors. The aim is not to achieve productivity gains or complete project in-sourcing, but rather to incrementally reduce the reliance on external contractors. This approach is most effective in areas such as business analysis, PMO, translation, and regulatory document creation. By leveraging GenAI, internal staff can access on-demand expertise, reducing the need for these external engagements and cutting direct costs by eliminating third-party invoices.
Managed services recontracting: Traditional outsourcing providers rely on knowledge asymmetries and high switching costs to maintain price premiums. GenAI disrupts this by compressing the learning curve for new service providers, especially in contact centers, service desks, and application support.
Large language models help new vendors quickly acquire organizational knowledge, reducing risks and disruptions associated with switching providers. This gives CIOs stronger negotiating leverage, enabling them to seek competitive bids from lower-cost providers who can swiftly become competent. Switching suppliers often entails increased risk; however, leveraging GenAI strategically within the service desk can mitigate this by accelerating the learning curve and enhancing time-to-value. This reduction in risk makes transitioning to a new supplier more viable, and if the supplier offers lower costs, it can lead to significant savings for the CIO.
To effectively manage services recontracting, CIOs should first assess incumbent lock-ins by identifying key managed services contracts where existing providers leverage their institutional knowledge for price advantages. CIOs should invite competitive bids from challenger providers and compare these with incumbent costs, urging incumbents to match or beat the offers. By utilizing GenAI to flatten the learning curve for new vendors, CIOs can enhance their bargaining power and achieve direct reductions in IT service costs.
Unlock Enterprise-wide Cost Reductions
There are three tactics CIOs can use to implement a financial efficiency strategy in nontechnology functions to reduce enterprise-wide budgets and save cash.
Working capital reduction: Excess working capital ties up cash that could be used for innovation or debt reduction and is a significant boardroom topic. CIOs can leverage GenAI-based predictive analysis to improve sales and accounts payable forecasts, reducing the need for idle working capital. By identifying patterns and utilizing unstructured data, and most importantly identifying new predictive factors, GenAI enhances forecast accuracy, enabling CFOs to reduce reserves and redirect funds to growth initiatives.
Improved forecasting directly reduces financial overhead. This approach offers immediate cost savings, especially in industries like insurance, aviation, and government, where capital reserves are crucial.
To reduce working capital, organizations should provide GenAI with comprehensive historical finance data to identify patterns and anomalies that enhance forecast accuracy. This enables CFOs to confidently adjust cash buffers, reducing reserves and freeing cash for growth or cost reduction. It’s crucial to track and evaluate the reinvestment of freed cash to assess the strategy’s effectiveness.
Revolving debt expense reduction: Revolving debt bridges cash flow gaps but incurs high interest costs. GenAI-driven cash flow forecasting helps CIOs and CFOs reduce reliance on expensive short-term financing by refining projections for strategic payment timing and reduced credit line usage, lowering interest expenses. Even small interest cost reductions can yield significant cash benefits without operational changes.
By integrating GenAI with enterprise planning systems, organizations can transform it into a strategic asset that frees funds for innovation and reduces operational costs. To implement this tactic, finance teams should map cash flow timing, deploy GenAI for precise forecasting, and track interest savings directly in the income statement.
Stronger contracts and revenue leakage reduction: Revenue leakage is a significant financial drain caused by weak contract terms, poor contract management, or unenforced pricing adjustments.
GenAI-assisted contract analysis provides a scalable solution by quickly identifying weak terms, ambiguous clauses, and invoice undercollection patterns. It can strengthen contracts to increase revenue and reduce losses, as demonstrated by an electronics manufacturer facing revenue loss due to inadequate pricing provisions.
CIOs should work with general counsel and finance teams to input historical contracts and performance data into GenAI, which can propose renegotiations and highlight anomalies. This leads to increased revenue and benefits the bottom line.
Takeaway
CIOs should reposition GenAI as a strategic financial tool focused on measurable savings. By focusing GenAI investments on direct financial outcomes, GenAI becomes a powerful instrument for enhancing fiscal management and achieving near-term ROI, especially crucial in increasingly uncertain business environments.