As federal agencies expand their AI initiatives and emphasis for efficiency under new White House guidance, there's growing focus on demonstrating the value and impact of technology investments. Agencies can proactively strengthen their position through systematic documentation of AI spending and outcomes. SoKat's system for measuring ROI in AI use cases helps agencies quantify and demonstrate the concrete benefits of their AI investments through rigorous metrics and analysis. Happy to connect and discuss our latest research findings and ROI system further!
?? Measuring AI's Value in the Era of Rapid AI Adoption The January 2025 Executive Order (EO) titled “Removing Barriers to American Leadership in Artificial Intelligence” and other recent federal initiatives herald more than just another technology initiative - they represent the most ambitious attempt yet to bring Silicon Valley-style metrics to federal operations. For agencies and contractors alike, the ability to demonstrate AI's concrete value has suddenly become a defining imperative - but where is the standardized framework across federal agencies for evaluating the ROI on AI use cases? Introducing SoKat's McIntyre & Liew Model (MLM): In response to this absence of a rigorous approach to benchmark the return on AI investments, Jim Kyung-Soo Liew, Ph.D., together with his co-researcher, leveraged decades of quantitative analyst expertise on Wall Street and leadership in federal change management to develop the McIntyre & Liew Model (MLM, patent-pending). This framework transforms the evaluation of AI's impact in government into a data-driven science. Drawing from 1,754 federal use cases, the MLM offers agencies and contractors a methodical approach to evaluating AI investments, enabling strategic resource deployment and the prioritization of high-impact projects. ?? The Science Behind the MLM: ?? Eight Quantifiable Dimensions: Breaks down benefits and costs into actionable scores. ?? Data-Driven Rigor: Refined through extensive federal AI use case analysis. ?? Actionable Insights: Optimizes resource allocation and highlights high-impact investments. ?? Research Results: The analysis reveals that agencies achieve optimal results not through bespoke solutions, but by adapting commercial-grade AI capabilities to government challenges - a finding that aligns well with the government’s recent efficiency mandate. ??? For Federal Agencies: ??Measure Outcomes: Convert technology initiatives into quantifiable results. ??Enhance Efficiency: Map gains with statistical precision. ??Boost Accountability: Use metrics that resonate with oversight bodies. ??Transform Missions: Shift from abstract goals to measurable impact. ?? For Government Contractors: ??Identify Opportunities: Evaluate AI projects with analytical clarity. ??Quantify Gains: Express efficiency improvements in compelling terms. ??Document Results: Back up outcomes with statistical validity. ??Demonstrate Value: Deliver clear, quantifiable value to your stakeholders. ?? Connect with us to explore how the MLM framework can help clearly demonstrate your technology's value in today's AI-driven efficiency environment. #GovernmentEfficiency #AIinvestment #RapidAIAdoption #SmallBusinessExcellence #DataDriven #ChangeManagement #QuantitativeAnalysis #SoKat SoKat