A 2026 Deloitte survey of more than 140 manufacturers found that 84% are already generating measurable value from AI, yet only about one in five use cases has been scaled across sites or the enterprise. For manufacturers, AI’s potential goes far beyond drafting emails or summarizing documents. It can help forecast demand, optimize inventory, identify production inefficiencies, predict equipment maintenance, analyze product margins and improve financial decision making. Used thoughtfully, it can provide faster operational insights and help employees focus on higher-value work.
But adopting AI without the right safeguards can also expose a company’s most valuable information. Manufacturers hold confidential customer data, supplier pricing, product specifications, employee records, banking information, tax documents and proprietary production processes. Entering that information into an unapproved public AI platform may create security, confidentiality and compliance risks.
The goal should not simply be to “use AI.” It should be to solve clearly defined business problems in a secure, measurable and controlled manner.
START WITH THE OPERATIONAL CHALLENGE
Manufacturers should begin by identifying where delays, manual processes or incomplete information are affecting performance. AI may help analyze historical sales and purchasing patterns to improve demand forecasting. It can flag slow-moving or obsolete inventory, identify unusual changes in material usage, and highlight products or customers with declining margins.
Consider a manufacturer that analyzes five years of equipment logs and discovers that the same combination of temperature, vibration and maintenance warnings repeatedly appears several weeks before a production-line failure. Management can then schedule maintenance before a breakdown rather than react after production stops.
In the accounting department, AI can assist with invoice processing, account reconciliations, cash-flow forecasting and the review of unusual transactions. These applications can reduce repetitive work, but they still require accurate source data and appropriate human review.
BUILD SECURITY INTO THE PROCESS
Before implementing an AI tool, management should understand what information the platform will access, where the data will be stored, how long it will be retained, and whether it may be used to train an external model. Business-grade platforms should be evaluated by qualified IT and security professionals before employees are authorized to use them.
Companies should establish a written AI acceptable-use policy explaining which tools are approved, what information may be entered and which activities are prohibited. Sensitive information should be classified, and access should be limited according to each employee’s responsibilities. Multifactor authentication, activity monitoring and appropriate audit trails should be part of the control environment. Employees also need practical training to recognize sensitive data and understand the risks of using unapproved applications.
KEEP PEOPLE ACCOUNTABLE
AI can identify patterns and make recommendations, but it should not have sole authority over financial, operational or compliance decisions. Management remains responsible for the accuracy of financial reports, the protection of confidential information and decisions made using AI-generated output.
Human review is particularly important when AI is used for product costing, inventory valuation, vendor selection, credit decisions, tax matters or financial forecasts. AI output can be incomplete or incorrect, especially when the underlying data is inconsistent. Manufacturers should document who reviews the results, how exceptions are investigated and when management approval is required.
MEASURE THE RESULTS
Every AI initiative should have a defined objective. Success may be measured through reduced equipment downtime, faster monthly closes, lower inventory carrying costs, improved forecast accuracy or fewer processing errors. If the benefit cannot be measured, the company may be adding technology without improving the business.
AI can become a meaningful competitive advantage for manufacturers, but efficiency and security must advance together. The strongest implementations bring operations, finance, IT and leadership to the same table. With reliable data, clear policies, appropriate controls and human oversight, manufacturers can work smarter while protecting the information and trust on which their businesses depend.
Kevin Forootan, CPA/CGMA is managing partner at MyCPA, LLP. Learn more at mycpallp.com.
