The death of spreadsheets: 6 reasons why AI will soon be the dominant business reporting tool

As many as 83% of decision-makers expect to increase investment in artificial intelligence (AI) during the next year, according to research from Salesforce. 

Services organizations are leaning into AI and automation, including assessing the current tools used to operate the business. Most services organizations are investing in AI. Eighty-three percent of decision-makers expect this investment to rise over the next year, while only 6% say they have no plans for the technology. 

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Generative AI use is on the rise -- 24% of service employees have used generative AI. The benefits of AI investments in service are clear. More than nine in 10 organizations with AI report cost and time savings. The top five use cases for AI in service are: customer-facing intelligent assistants, automated summaries and reports, service responses, agent-facing intelligent assistants, and intelligent offers and recommendations. 

AI's benefits extend to forecasting and reporting, including primary use cases in professional services. While the widespread adoption of AI is still in its early stages, 93% of service professionals at organizations investing in AI say the technology saves them time on the job.

In professional services, spreadsheets have long been the duct tape of operations: pervasive, flexible, and too often held together by repetition and sheer force of will. Whether calculating billable utilization or acting as a forecasting tool for services revenue, spreadsheets are the default lens through which many firms view their business. But that lens is rapidly fogging up.

Today, AI is not just a complementary tool, it is on a path to becoming the core decision engine for services organizations. We predict that, by 2027, AI will replace spreadsheets as the dominant method for utilization reporting and revenue forecasting -- and it might happen faster. Here are six reasons why AI will replace spreadsheets for forecasting and reporting. 

1. Spreadsheets are not the answer

Let's be honest: spreadsheets were designed in the era of floppy disks, dial-up modems, and fax machines. They were never meant to handle the variety and volume of data in modern services businesses.

Forecasting with spreadsheets today means stitching together data from time-tracking tools, CRM systems, and project management or professional services automation (PSA) software. That effort is without even considering the numerous other spreadsheets organizations use to track their issues. 

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This process is time-consuming, error-prone, and brittle. What happens when a services firm with 500+ resources needs to adjust forecasts mid-quarter based on shifting client priorities or economic uncertainty? That's not a spreadsheet job. That's a nightmare for the head of service operations.

Spreadsheets aren't the answer. Instead, they are part of the problem. In a recent survey by researcher Forrester of more than 600 profession services leaders, four of the top five challenges faced were tied to spreadsheets: lack of visibility around plan vs actuals on projects, multiple data sources generating conflicting insights, the absence of common definitions for metrics/KPIs, and an inability to obtain insights around forecasting.

AI doesn't sleep. Trained on live data from across the enterprise, it ingests, correlates, and predicts outcomes in real time to eliminate manual updates, late-night data pulls, and the "someone forgot to refresh the pivot table" debacle before the board meeting.

2. Utilization is a moving target

In professional services, utilization is often the core metric to be tracked and optimized, with over 99% of professional services organizations believing that improving the utilization rate is possible. However, traditional utilization reporting is a rear-view mirror exercise. It tells you what already happened, not what's about to happen, and is a difficult calculation for most organizations today. 

AI changes that process. By consuming real-time timesheet entries, project pipeline changes, and historical patterns, AI models can predict utilization before it drops, at a regional, practice, group, or even individual level, allowing leaders to reassign, reprioritize, reinforce, or retrain staff in time to make a difference.

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For example, AI can spot that a high-billable consultant is about to roll off a project with no upcoming allocation. Instead of learning about this issue after the fact via a spreadsheet next month, the AI alerts the PMO or resource manager today. That's not reporting. That's prescription and prevention.

3. Forecasting revenue requires nuance

Forecasting services revenue isn't just about multiplying hours by rates, it's about understanding project win rates, client behavior, resource availability, and market conditions simultaneously. That level of complexity makes spreadsheets inadequate and dangerous, as much of that data lives in many systems with multiple definitions, data types, and levels of data granularity. Most organizations can't forecast beyond a month, with the vast majority, 91%, pointing to "old, unactionable data" as having the largest impact.

AI thrives in this probabilistic arena. It can weigh dozens (or hundreds) of variables, learn from past wins and losses, and continually refine forecasts as new data rolls in. A good AI model can detect patterns invisible to humans, such as which clients are most likely to delay projects or payments, or which project types or individuals tend to overrun budgets by 20%.

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Instead of "Version 17_final_FINAL.xlsx," you get a living, breathing forecast that updates itself, flagging risks, opportunities, and anomalies as they arise, while showing its work rather than just a set of numbers.

4. Services teams don't have time

Ask any services operations lead what they spend half their week doing, and they'll tell you: chasing data, cleaning data, validating data, and cutting and pasting data columns or cells, just so that leadership can get "one more version" of the utilization report.

This approach isn't sustainable or desirable. Manual reporting processes combined with the time and difficulty of bringing data together were cited as three of the top four challenges for professional services organizations. 

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With AI integrated directly into the operational stack via PSA, ERP, and CRM, data flows continuously and intelligently. AI-powered analytics platforms can surface key metrics and trends via natural language queries, such as "What's our projected utilization for Q3?", eliminating the need for error-prone, time-consuming, and risk-generating manual slicing and dicing.

As the war for services talent intensifies, no one wants their highly paid business analysts or practice managers acting as spreadsheet jockeys. The opportunity cost is enormous.

5. AI brings insights

Here's the rub: spreadsheets tell you what happened. AI tells you why it happened and what's likely to happen next. That shift alone should convince you to stop using spreadsheets to understand your issues with service delivery.

Modern AI tools use explainable machine-learning models to provide context alongside predictions. When utilization is forecast to dip in the second fiscal quarter, the AI won't just throw out a number, it will attribute the drop to fewer opportunities in the first fiscal quarter, attrition in the European delivery team, and delayed project starts from two key clients. 

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Could your team have reached these answers with spreadsheets and heroic effort? Sure, but that level of insight in a sustainable, let alone timely, fashion is simply out of reach for both spreadsheets and traditional business intelligence tools.

Even better, AI can easily generate "what if?" scenarios to provide solutions. What if we accelerate hiring by 30 days? What if we shift the North America team to support Europe? These simulations help services leaders make faster, more confident decisions based on current conditions.

6. Spreadsheets are a compliance risk

Finally, let's consider risk. Inaccurate utilization and revenue forecasts don't just make you look bad, they can result in missed earnings targets, misallocated bonuses, and blown budgets.

Spreadsheets are notoriously hard to audit, easy to manipulate, and susceptible to version drift and "walking out the door" in the hands of disgruntled employees. AI-based platforms, in contrast, offer full data lineage, audit trails, and permissioned access, which is crucial for public companies concerned about data leakage or firms managing regulated engagements.

As CFOs and CROs tighten the screws on forecast accuracy and defensibility, spreadsheets are hammers treating everything like a nail.

Where the industry goes next

Leading PSA (Professional Services Automation), CRM, and ERP vendors are embedding AI into forecasting and planning workflows. This isn't a theoretical future, it's here.

The 80% of firms still clinging to spreadsheet-based planning and forecasting will find themselves at a competitive disadvantage, unable to respond fast enough to shifting client needs or resource constraints. The winners in the next wave of services growth will be those who see forecasting and reporting as a capability, one that must be intelligent, autonomous, and always-on.

The promise of AI and the successful adoption of this emerging technology will depend on organizational data and AI literacy. The promise of AI and data is its ability to scale positive business outcomes. Business leaders must invest in and develop integration strategies, knowing that AI cannot function at its best without access to trustworthy data. Business leaders must also invest in employee training, deliberately focusing on improving data literacy for all stakeholders. 

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To summarize, the era of spreadsheet supremacy is over. AI has entered the chat, and it's not here to assist your outdated manual processes, it's here to replace spreadsheets and make your people better.

Professional services firms can't afford to navigate with analog tools in a digital world. Spreadsheets are useful for ad hoc analysis and back-of-the-napkin modeling by individuals, but as the foundation for core business forecasting at an enterprise level? The clock has run out.

AI doesn't just make forecasting and utilization reporting faster, the technology makes processes smarter, more resilient, and more predictive. The firms that embrace this shift now will build a strategic edge that can't be copied or pasted.

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This article was co-authored by Joe Thomas, enterprise solution director and global analytics evangelist, Certinia.