Whether you're the founder of an AI company or a traditional software company, the business case and ROI are more required than ever. This isn't new, but the quality bar for ROI is much higher than before.
You'll often hear statements like, "We helped your team save 2 hours, leading to $X savings per year." If you did the math across all vendors making such claims, companies would benefit more from buying software than from selling their own products. That doesn't make the use case invalid — but the context of the savings and impact must be more explicit than ever.
There are three main areas where impact lives in a business case: increase revenue, reduce cost (or maximize efficiency), or reduce risk. Below are examples for both replacing an incumbent and for "category creators," assuming you have the technical win.
Start with an overview of the business case
How does this tool help the company meet its objectives for the year?
- Replacing an incumbent: Customer's internal OKR — "Profitability by 2025: reduce software spend by 20%."
- Category creator: Customer's internal OKR — "Use AI across all departments by end of H1 to do more with our existing headcount."
What is the current problem you're solving?
What problem does the company have related to what you solve? What can it not do technically that makes your solution differentiated? If an existing solution is in place, why do they need to buy from you — and are there "consolidation alternatives" you need to address? Where has there been a negative impact or repeated wasted cost that your solution would alleviate?
Why does this need to be solved now?
- Replacing an incumbent: Renewal of the competitor is two months out with a 30-day opt-out. We have a preference for the new solution, with the evaluation results below.
- Category creator: We're releasing feature X this quarter and need at least 45 days to implement. Buying now lets us release on time and improve the capabilities of "Big Bet #1" mandated by our CEO.
Tie it together with a value driver
Increase revenue
- Replacing an incumbent: After the evaluation, we learned this allows for more accurate forecasting and optimization of resources. In the POC, we saw a 15% improvement in accuracy, an estimated $800,000 in additional revenue.
- Category creator: Our AI agent had 95% response accuracy and reduced wait times. Higher NPS and retention increase customer lifetime value by 20% on average — an estimated $500,000 in additional revenue.
Reduce cost (or maximize efficiency)
- Replacing an incumbent: During the evaluation, we ran the workload in one-third the time. This optimization can cut cloud computing costs by 30%, saving approximately $1.2 million.
- Category creator: Using AI agents on our support team lets us resolve 4x more tickets per shift without additional hiring. Rather than reducing headcount, we can reallocate the $1.5 million in support hiring toward other initiatives.
Reduce risk
- Replacing an incumbent: Using modern machine learning and real-time threat intelligence, we identified threats our current solution missed. This can reduce the risk of data breaches by 40%, protecting against potential losses and regulatory fines that could reach $2 million annually.
- Category creator: Before using an AI agent, we couldn't dynamically find threats at this scale. During the POC, we reduced the risk of successful attacks by 30%, avoiding potential losses estimated at $800,000 per year.
By doing the above, you put yourself in a far more defensible position on the business case. Many other tactics are necessary throughout the sales cycle, but having this well-prepared toward the end significantly increases the likelihood of closing.