This article was based on the interview with Tommi Marsans, Verizon Business Group Transformation Lead by Greg Kihlström for The Agile Brand with Greg Kihlström podcast. Listen to the original episode here:
Prioritizing impactful use cases for Artificial Intelligence implementation in a B2B setting is crucial for achieving success and maximizing the return on investment. In the podcast, Tommi Marsans, a marketing technology strategist at Verizon Business Group, shares her team’s approach to selecting use cases that would have immediate impact.
The first step in prioritization is to focus on use cases that will deliver immediate benefits. Instead of trying to tackle all possible use cases at once, it is important to identify specific areas where AI can make a significant difference. By starting with these use cases, organizations can quickly demonstrate the value of AI implementation and generate a positive return on investment.
In the case of Verizon Business, they chose use cases that would directly impact their bottom line. They looked at factors such as the number of units saved or sold, as well as the cost of retaining or acquiring customers. By considering these factors, they were able to prioritize use cases based on the potential benefit to the business.
By prioritizing impactful use cases, organizations can also ensure that they are addressing the most critical challenges or opportunities they face. This approach allows them to focus their resources and efforts on areas that will have the greatest impact on their business outcomes.
Additionally, prioritizing impactful use cases helps organizations build momentum and gain support for further AI implementation. By delivering tangible results and demonstrating the value of AI, organizations can generate enthusiasm and support from stakeholders, making it easier to secure resources and expand AI initiatives.
However, it is important to note that prioritization is an ongoing process. As organizations gain experience and gather data from initial AI implementations, they can refine their prioritization criteria and identify new use cases with even greater potential impact. This iterative approach allows organizations to continuously optimize their AI implementation and drive continuous improvement.
Prioritizing impactful use cases for AI implementation is essential for achieving success and maximizing the return on investment. By focusing on specific areas where AI can deliver immediate benefits and considering factors such as units saved or sold and customer acquisition or retention costs, organizations can prioritize their efforts and generate tangible results. This approach not only helps organizations address critical challenges or opportunities but also builds momentum and support for further AI implementation. By continuously refining and iterating their prioritization criteria, organizations can drive continuous improvement and ensure the long-term success of their AI initiatives.