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There’s a big risk with AI and it's not the one you are thinking of. Putting security concerns aside, there’s a big risk of AI projects failing to deliver any real business value. Like many technologies before it, AI shouldn’t be implemented for its own sake or as an IT tick box exercise.
This risk is amplified by the hurry to launch AI initiatives quickly in response to the urgent AI mandate from every board worldwide. Our guidance to everyone working on this right now is to focus on business impact right from the start.
Results matter
The appetite for AI is huge, but simply deploying AI for the sake of it won’t deliver significant value. What really matters is the impact it has on your business. Does it save time? Cut costs? Increase sales? Measuring ROI on your AI initiative helps you see the real value behind the technology.
Make better business decisions
AI projects can be expensive. You’re spending money on tools, training, and data. Without tracking ROI, it’s hard to know what’s working. With it, you can focus on the AI solutions that give you the best results and stop wasting time on the rest.
Earn trust and support
Business leaders want proof, not just potential. Showing that an AI tool brings real returns builds trust and makes it easier to get support for future projects. People are more likely to back something that clearly works.
Scale what works, drop what doesn’t
When an AI initiative proves its worth, you can use it in other parts of your business with confidence. The data backs you up. At the same time, if something’s not delivering, you’ll know when to pivot or pull back.
Data quality and accessibility
AI needs to be trained on high-quality, relevant and clearly labelled data to deliver reliable outcomes. Poor data quality leads to inaccurate predictions, higher costs for data cleaning, and slower time-to-value, significantly reducing ROI.
Use cases
Selecting the right use case has a big impact on the benefits AI can deliver. Gartner’s How to Calculate Business Value and Cost for Generative AI Use Cases, Feb. 2024 report showed that GenAI has the potential to save between ~$7,000,000 to $16,000,000 per year among business users and only ~$160,000 to $600,000 per year among developers. Therefore, AI efforts should prioritize increasing the productivity of the larger group of non-technical users in an organization. But the reality in the enterprise today is that faster coding is one of the most common applications. This highlights a huge untapped opportunity for driving AI adoption across the rest of the enterprise.
Adoption
Even the best AI solution won't deliver ROI if it's not embraced by others across the business. Low adoption rates limit the operational and strategic benefits of AI, making it harder to justify the investment. A powerful way to combat this is to implement Gen AI within a wider project, and as part of the business process. The clearest example is a process automation project, which creates the right context for not only driving the adoption of AI, but also deploying it in a way that is governed and secure.
Deliver tangible ROI on your AI initiative with Bizagi
Cost savings:
Hours of manual work eliminated
Identify repetitive or labor-intensive tasks automated by AI.
Formula: Hours Saved x Average Hourly Wage = Cost Saved
Example: Automating data entry saves 500 hours/year at $30/hour = $15,000/year.
Cost of errors or rework reduced
AI reduces human error in areas like data processing, manufacturing, or customer service.
Formula: Reduction in Error Rate x Cost per Error = Savings
Example: AI reduces product defects by 20%, saving $50,000/year in returns and rework.
Operational efficiency gains
AI streamlines supply chains, logistics, scheduling, and other processes.
Formula: Compare throughput, costs, or cycle times before and after AI implementation.
Example: AI-powered logistics optimizes routes, cutting fuel costs by $25,000/year.
Revenue growth:
Increased sales or conversion rates
AI personalization, recommendations, or chatbots improve conversion.
Formula: (New Conversion Rate - Old Rate) x Traffic x Average Sale = Additional Revenue
Example: AI raises conversion from 2% to 2.5% on 100,000 monthly visitors = $25,000/month increase.
Higher average transaction value
AI upselling or dynamic pricing can boost order sizes.
Formula: (New Avg Order Value - Old Avg) x Number of Transactions = Additional Revenue
Example: AI increases average sale from $80 to $85 across 10,000 orders = $50,000 gain.
New revenue streams unlocked by AI
AI enables new products, services, or business models (e.g., AI-as-a-service, predictive maintenance).
Assessment: Measure income generated from offerings that would not be possible without AI.
Time saved
Tasks completed faster (before vs. after)
Compare process completion times pre- and post-AI.
Formula: Time Saved per Task x Number of Tasks = Total Time Saved
Example: AI reduces invoice processing from 30 mins to 5 mins for 5,000 invoices/year = 2,083 hours saved.
Fewer process bottlenecks
AI helps streamline approvals, handoffs, or decision-making.
Assessment: Track reduced delays in workflows or project delivery timelines.
Shorter decision or delivery times
AI provides real-time insights or automates parts of decision-making.
Impact: Faster responses can improve competitiveness, customer satisfaction, and agility.
Accuracy & quality
Fewer customer complaints or returns
Better product/service accuracy leads to fewer errors and higher satisfaction.
Formula: Reduction in Returns x Cost per Return = Savings
Example: AI improves product match accuracy, reducing returns by 500 units/year = $10,000 saved.
Better forecast accuracy
AI improves predictions for demand, supply, and customer behavior.
Assessment: Compare forecast error rates before and after AI use, and measure inventory or planning cost impacts.
Improved customer ratings or satisfaction scores
AI chatbots, personalization, and automation improve user experience.
Assessment: Track changes in CSAT, NPS, or star ratings and correlate with retention or repeat business.
An asset management company used agentic automation within their accounts payable process and achieved a 93-95% reduction in invoice processing time, saving ~16,500 hours annually.
Another in the same industry used agentic automation for service requests and achieved an 88% reduction in processing time, saving ~6,667 hours annually.
Tracking the ROI of your AI investment tells you what’s working, what’s not, and where to scale up. By looking at cost savings, time back, and quality improvements, you get a clear picture of AI’s true impact.
Bizagi's AI capabilities are helping businesses boost productivity and create better experiences for their employees and customers.
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