How To Assess Generative AI ROIHow To Assess Generative AI ROI
A structured approach requires detailed cost-benefit analysis.
March 3, 2025
Last month on No Jitter I shared insights into how companies are measuring ROI for their adoption of generative AI collaborative assistants. In this month’s post, I want to dig a bit more into the methodology for assessing generative AI’s value.
Building the Organization
The primary requirement for AI success is having an organization in place to drive AI adoption. Metrigy’s AI for Business Success: 2024-25 study of 697 organizations found that just 35.5% of organizations had established an AI “Center of Excellence” as of early 2024 (stay tuned for our 2025 report in early Q2). Those in our success group, defined as having at or above average ROI for their AI investments, were 70% more likely to have an AI center of excellence versus those with no or low ROI.
An AI center of excellence is typically comprised of a team of people with complementary skillsets and responsibilities who provide expertise, best practices, training, and guidance for AI decisions. The team tracks technology innovations and how they apply to the company to gain efficiencies and drive additional business metrics, including revenue, profitability, customer satisfaction, and employee loyalty. Given their knowledge of the business, an AI center of excellence is especially well equipped to understand the positive benefit that AI can bring to specific workflows and business activities.
Building the ROI Calculation
Once the right organization is in place the next step is to build an ROI analysis model. Basic ROI is of course “value minus cost” with positive ROI being achieved if value exceeds cost.
Cost Variables to Consider
Starting with the cost side of the equation, companies should consider the following:
Administrative Support: This includes staff (or third party) time for implementation, configuration, and on-going management as well as end-user support. Administrative support will vary depending on the needs of the organization but typically includes time spent configuring permissions, creating support documentation for help desk staff, and monitoring Gen AI for potential security issues.
Compliance: Includes policy creation, capture and archiving of Gen AI created content including documents, meeting summaries, transcripts.
Licensing cost for generative AI add-ons: Not every vendor charges for generative AI virtual assistants, but some do, and this cost needs to be factored into any ROI determination.
End-user training: This could include either formal or informal training, typically on a regular basis to ensure employees are up to date on new features as they become available.
Ongoing monitoring: Companies will typically want to assess if and how employees are using generative AI tools to identify potential adoption challenges and concerns, and to align training and administrative support functions with user needs.
Ways to Measure Value
Now that we have the costs out of the way, let’s look at some ways that generative AI can return value to the organization. As I noted in my previous post, these usually include cost savings, revenue increases, and productivity improvements. Here are some examples.
Cost savings: Generative AI virtual assistants may reduce costs by improving staff efficiency, thus reducing existing staffing needs, the need for additional staff, or the need for third-party services. For example, a generative AI translation capability could reduce the need to hire translators or use a third-party translation service.
Revenue increases: These typically come from using generative AI to improve sales processes. Examples could include chat summarization to respond more quickly to sales opportunities, or workflow automations that shorten sales cycles.
Productivity improvements: Often these are the easiest to quantify. Examples include reducing the time spent catching up in the morning, eliminating the need for manual note taking within meetings, and improving the ability to find information across a variety of collaboration channels.
These examples are somewhat generic. Building an accurate ROI calculation requires a deep understanding of your specific business activities – as an AI center of excellence would have – to identify ways that generative AI virtual collaboration assistants can provide measurable business benefit. It is important to look at not just every day, repeatable activities, but also activities that may vary on a seasonal or annual basis. For example, a company that can use a generative AI virtual assistant to summarize and highlight voicemails may see more value during peak business time than they do during off-peak times.
What about Soft Benefits?
Generative AI virtual assistants offer additional benefits that are difficult to quantify. Ensuring that everyone is aware of key topics discussed at a meeting and follow-on action items may not lead to quantifiable business benefits that are easy to measure, but they may improve the ability for meeting participants to focus on meeting discussions without having to worry about capturing what was said. This would presumably lead to more efficient (and perhaps shorter) meetings that are focused on solving problems and making effective decisions.
Further, analytics that look for keywords and topics across company chats may provide business leaders with insights into challenges and opportunities that could lead to further action with measurable benefit. Again, understanding soft benefits requires intimate knowledge of the organization.
Next Steps
As noted above, step one is to create an organization charged with determining the ROI for generative AI virtual assistants. From there, it is critical to identify all costs, and all potential business benefits. But determining ROI isn’t a one-time exercise. Consider implementing an approach, led by an AI center of excellence, that continually revisits costs, assumptions, and business benefits and that monitors AI adoption to identify areas requiring attention.
—
About Metrigy: Metrigy is an innovative research and advisory firm focusing on the rapidly changing areas of workplace collaboration, digital workplace, digital transformation, customer experience and employee experience—along with several related technologies. Metrigy delivers strategic guidance and informative content, backed by primary research metrics and analysis, for technology providers and enterprise organizations
About the Author
You May Also Like
