RSMUS.comRSM’s Rapid AI Deployment: A Year of Strategic Impact Across Industries
In the fast-evolving landscape of Artificial Intelligence (AI), where, according to Harvard Business Review, between 60% and 73% of enterprise data remains untapped, RSM stands out for its effective and impactful mobilization in delivering AI solutions.
While RSM has been helping clients strategize, build, and deploy AI and Machine Learning (ML) solutions before ChatGPT’s release, the Generative AI capabilities made known through ChatGPT opened a new world of value drivers for clients.
As we approach the 1st anniversary of ChatGPT’s release, we want to reflect on case studies from the past year that demonstrate our commitment to staying on the cutting edge of AI research and delivering high quality for our clients. From revolutionizing organizational processes to optimizing business functions, these success stories underline RSM’s commitment to deploying AI the right way.
Optimizing Processes and Driving Economic Development with Azure OpenAI Services
Two standout examples of RSM’s rapid mobilization around AI were demonstrated working alongside the City of Kelowna to 1) create an AI solution to facilitate the building permit process and 2) create an AI Grant Writing Assistant application to help the Grant Management team procure budget dollars for the city. Both use cases helped the City of Kelowna drive economic development and reduce the tax burden on its citizens through the use of AI.
The automated response creation and enhanced user experience significantly boosted the capacity of staff to handle a greater volume of applications within the same timeframe. Beyond quantitative gains, the Generative AI tool played a crucial role in unifying the voice and mission in the grant application process and standardizing the building permit process, which fostered trust among stakeholders.
To learn more about the successful partnership between the City of Kelowna, Microsoft, and RSM, check out this webcast on empowering smart cities with AI.
Leveraging millions of external datasets to boost forecasting and demand planning
In another compelling use case, RSM assisted a client in the food industry with enhanced forecasting capabilities. The client struggled with its demand planning processes and had not been able to correlate external data with its sales performance successfully in the past. RSM utilized Azure Machine Learning and Prevedere to look at many prior years of sales data, by product, by customer, at a weekly level of granularity when needed, and correlate with three million macroeconomic datasets. The client was then provided with weekly and monthly planning numbers alongside macroeconomic leading indicators that were most significant in impacting their sales. Empowered with this AI analysis, the client is able to proactively adapt to ever-changing market conditions.
Identifying at-risk customers with machine learning
In an adjacent AI project, RSM helped a client predict member churn to prevent their members from becoming inactive. Member inactivity directly results in revenue loss, so it was critical to rapidly develop a machine-learning model to flag these at-risk customers.
RSM developed a machine learning model in Azure, seamlessly integrating the model into the client’s operational framework. The model processed internal data to generate predictions that were fed into a Power BI dashboard. This integration not only streamlined the flow of information but also empowered business users with insights for making informed decisions on which members to target.
The accelerated timeline from project initiation to model implementation (less than 8 weeks) was indicative of our commitment to providing timely and impactful solutions, ensuring that actionable insights are not just generated but utilized effectively for strategic decision-making.
Automated Compliance Management for Internal Audit with Generative AI
To help clients handle an evolving regulatory landscape, the RSM team has developed an automated compliance management solution with OpenAI’s GPT-4 model. The solution helps Internal Audit departments compare their internal controls against regulations applicable to their organization and assess the current level of coverage. If there are gaps in the controls, the generative AI model can develop and recommend a control to help meet regulatory requirements. With a custom-built user interface, users can also refine existing control language when needed and view dashboards to assess performance at a portfolio level. All prompts seamlessly communicate with the AI backend to provide responses to necessary tasks, streamlining the internal audit process and enhancing compliance management.
Enhancing predictions with generative AI and computer vision
In recent work with a public sector organization, RSM used generative AI to review and label datasets to predict flooding levels and create a proactive alert system to help employees and citizens become more resilient to flooding. This is critical to help the city utilize precious resources in an efficient manner.
In a second effort, the RSM team leveraged computer vision to classify images and optimize vehicle dispatch decisions for job sites. The effectiveness of the computer vision model saves the city time and money and can be quickly applied in other use cases.
RSM works quickly to deploy AI and maximize client investment
As enterprises face the reality that a significant portion of their data goes unused and value levers untapped, the RSM approach shows the effectiveness of utilizing and investing in AI technologies. RSM is at the forefront of AI development helping clients turn their data into valuable assets for their businesses.
Contact us today to see how RSM can help navigate your complex business challenges with AI.
By: Robbie Beyer and Pablo Orjales
