Measuring the Financial Return on AI Investments in Manufacturing
Artificial intelligence (AI) is creating new opportunities for manufacturers to improve efficiency, lower costs, and make better-informed business decisions. AI-powered tools are becoming more popular for uses from predictive maintenance and automated quality control to production planning and inventory management.
Implementing technology is only one part of the equation. For manufacturers operating in a competitive environment with ongoing pressures, the real question is whether these investments deliver measurable financial results.
Look Beyond the Initial Investment
There are many expenses that come along with an AI investment. These expenses include implementation costs, system integration, employee training, ongoing maintenance, and subscription fees, which can all affect the total cost of adoption.
Manufacturing businesses should consider these expenses alongside the potential benefits before implementation. For example, while predictive maintenance technology may help reduce unexpected equipment downtime, AI-assisted quality control may identify defects earlier in the production process. Both implementations may improve productivity, but the financial impact will depend on how well they are implemented and integrated into existing operations.
Developing a cost estimate before committing to an investment can help management establish realistic expectations and avoid overlooking expenses that may affect the project’s return.
Measure What Matters
A successful technology investment should support specific business objectives. Before adding an AI solution to the company, manufacturers should determine baseline performance measures and identify the results they expect to achieve.
Metrics for manufacturers to consider may be production costs per unit, scrap and rework rates, equipment downtime, labor productivity, inventory levels, and gross profit margins. The appropriate measures will vary depending on the company’s technology need and operational challenge it intends to correct.
For example, if a manufacturer invests in AI to reduce material waste, management should compare waste levels and associated costs before and after implementation. If the goal is to improve production efficiency, tracking throughout and downtime may provide more tangible results for the business to examine.
It is also important to distinguish projected savings from realized results. Improvements in one area do not automatically translate into higher profitability if other costs increase or production constraints remain.
Build a Strong Financial Business Core
Before moving forward, manufacturing companies should evaluate potential investments against their broader financial priorities. Return on investment, payback period, cash flow requirements, and the expected useful life of technology can all inform the decision.
A forecast analysis can help management understand how results may change if implementation costs exceed expectations, implementation takes longer than planned, or anticipated productivity fails to develop.
Regularly comparing actual performance with initial projections allows businesses to identify gaps, adjust implementation plans, and make more informed decisions about future investments. This ongoing evaluation is especially important when technology is introduced in phases or when benefits take time to develop.
Make Financial Insight Part of the Process
AI offers significant opportunities for manufacturers, but adopting new technology should not be the end goal. The focus should be on making strategic business decisions that improve operational efficiency and strengthen financial performance.
Manufacturers do not need to navigate these decisions alone. Find a professional who understands the financial and operational considerations manufacturers face when investing in new technology, as well as help evaluate how these investments align with broader plans, working capital needs, and long-term business goals.
At McKonly & Asbury, we help businesses evaluate investment costs, assess profitability, strengthen financial forecasting, and establish meaningful performance measures to support informed decision-making. Our team can help manufacturers gain the financial insight and guidance needed to evaluate technology investments, measure results, and focus on what matters most: sustainable growth, stronger profit margins, and long-term business success.
Please reach out to the Manufacturing & Distribution team for more information on the topic outlined above. For more information regarding our Manufacturing & Distribution practice, visit our Manufacturing & Distribution industry page.
About the Author
Laura Sherman is a Manager with the firm and a member of the Audit & Assurance Segment, servicing clients in the manufacturing and distribution and employee benefit plan industries.… Read more
