• Written by Azhar Aliyar, Director

A pharmaceuticals business buys a laboratory information management system, then a quality management system, then an enterprise resource planning system, and before long, the IT department is awash with requests for reports and dashboards to answer questions that the existing systems should already be able to answer. The cost of IT grows, not because the systems themselves are expensive to run, but because the business is forever building new reports and integrations to get the answers it needs.

Where IT money actually goes in a pharmaceuticals business

The majority of IT spending in pharmaceuticals goes towards getting data out of systems, rather than running the systems themselves. This is because each new question that the business wants to answer requires a new report, a new dashboard, or a new integration, all of which cost money and time to build and maintain. According to the US Census Bureau's Business Trends and Outlook Survey, 22.4% of US businesses reported using AI in the two weeks to July 2026, but in pharmaceuticals, the focus is often on using these systems to generate more reports, rather than to answer questions directly. A shift supervisor checks the maintenance log, while the category manager compares two suppliers, but the IT department is busy building reports to answer questions that could be answered by the systems themselves.

This approach is wrong, because it assumes that the systems are not capable of answering the questions on their own, and that a report or dashboard is always the best way to get the answer. In reality, many of the questions that the business wants to answer could be answered by the systems themselves, if only they were asked the right way.

The report and dashboard backlog

The report and dashboard backlog is a major cost driver in pharmaceuticals IT. Every time a new question is asked, a new report or dashboard is built, and this can lead to a proliferation of reports and dashboards that are rarely used. According to the US Census Bureau's Business Trends and Outlook Survey, 14.3% of US businesses used AI in sales and marketing in the previous six months, but in pharmaceuticals, the focus is often on using AI to build more reports, rather than to answer questions directly. This approach is not only expensive, but it also leads to a situation where the business is drowning in data, but unable to get the answers it needs.

A better approach would be to use AI to answer questions directly, rather than building reports and dashboards. This would not only reduce the cost of IT, but it would also provide the business with the answers it needs, when it needs them. For more information on how AI is being used in pharmaceuticals, see our blog post on the subject.

Extending LIMS, the quality management system, batch MES and ERP instead of replacing them

Rather than replacing existing systems, such as LIMS, the quality management system, batch MES and ERP, pharmaceuticals businesses could use AI to extend their capabilities. This would involve asking better questions of the systems, and using AI to get the answers. According to the US Census Bureau's Business Trends and Outlook Survey, 12.4% of US manufacturers, the Census sector that includes pharmaceutical makers, reported using AI in the previous two weeks, and this number is likely to grow as more businesses realize the benefits of using AI to extend their existing systems.

By extending existing systems, rather than replacing them, pharmaceuticals businesses can defer a replacement programme, and reduce the cost of IT. This approach also allows businesses to get more value from their existing systems, and to provide better answers to the questions that the business needs to ask. For more information on how to get the most from your existing systems, see our executive and strategic leadership page.

Integration spend

Integration spend is another major cost driver in pharmaceuticals IT. Every time a new system is bought, it needs to be integrated with the existing systems, and this can be a costly and time-consuming process. According to the US Census Bureau's Business Trends and Outlook Survey, 1.7% of US businesses used AI in production of goods in the previous six months, but in pharmaceuticals, the focus is often on using AI to integrate systems, rather than to answer questions directly. This approach is not only expensive, but it also leads to a situation where the business is spending more and more money on integration, rather than on getting the answers it needs.

A better approach would be to use AI to join data at the point of the question, rather than building and maintaining a point to point link for each one. This would not only reduce the cost of integration, but it would also provide the business with the answers it needs, when it needs them. For more information on how to reduce integration spend, see our contact us page.

Where AI adds cost rather than removing it

While AI can be used to reduce IT costs in pharmaceuticals, it is not a panacea, and there are some areas where it can add cost rather than removing it. For example, the data work and governance that is required to implement AI can be costly and time-consuming. According to the US Census Bureau's Business Trends and Outlook Survey, 64.3% of US businesses that already use AI made no change of any kind to adopt it, and only 6.8% changed how they collect or manage data, but in pharmaceuticals, the data work and governance required to implement AI can be significant.

However, this does not mean that AI is not worth implementing. Rather, it means that businesses need to be honest about the costs involved, and budget for them accordingly. By doing so, businesses can ensure that they get the most from their AI implementation, and that they are able to reduce their IT costs in the long run. For more information on how to budget for AI, see our analysis of the US Census Bureau's Business Trends and Outlook Survey.

How to tell whether IT spending actually fell

Measuring the success of an AI implementation in reducing IT costs can be difficult, but there are some key metrics that businesses can use. For example, businesses can measure the number of reports and dashboards that are no longer needed, or the number of integrations that are no longer required. According to the US Census Bureau's Business Trends and Outlook Survey, 11.4% of US businesses used AI in their information technology function in the previous six months, and this number is likely to grow as more businesses realize the benefits of using AI to reduce IT costs.

By measuring these metrics, businesses can get a clear picture of whether their AI implementation has been successful in reducing IT costs, and can make adjustments as needed. This approach also allows businesses to ensure that they are getting the most from their AI implementation, and that they are able to reduce their IT costs in the long run.

What this does not do

This approach to reducing IT costs in pharmaceuticals does not replace the need for good data governance and management. In fact, AI requires high-quality data to function effectively, and businesses that do not have good data governance and management in place may find that their AI implementation is not successful. According to the US Census Bureau's Business Trends and Outlook Survey, 61.6% of US businesses with no plans to adopt AI said it was not applicable to them, and only 6.9% said it was too expensive, but in pharmaceuticals, the need for good data governance and management is critical.

By understanding what this approach does not do, businesses can ensure that they are using AI in a way that is effective and efficient, and that they are able to reduce their IT costs in the long run. For more information on how to get started with AI, see our website.