Proving AI ROI: A Practical Framework for Enterprises

AI platforms are transforming industries by enhancing decision-making, automating tasks, and uncovering insights from data. However, like any significant investment, businesses need to assess the ROI to determine how the platforms drive value.

‍

Looking back, 2023 saw a surge in awareness around generative AI, and 2024 was a turning point for organizations deriving meaningful value from the technology. A McKinsey survey reports that 65% of organizations now use generative AI regularly, not just for one-off projects or niche applications. Over half of these organizations report deploying AI in multiple business functions, reflecting a more integrated approach to leveraging AI across the enterprise.

‍

The 2025 Enterprise AI Trends Report found that proven ROI is a top consideration for enterprises when evaluating AI solution providers. With about 50% saying AI is a board-level priority, signaling the importance of the right investment.

‍

Defining ROI

Traditionally, ROI measures financial profit from an investment, analyzing how long it takes to recoup the upfront costs and generate additional profit. However, with AI, ROI also encompasses  unseen benefits: improved employee engagement, higher retention rates, and enhanced customer satisfaction.

‍

For instance, IDC’s recent study found that companies realize an average return of $3.5 for every $1 invested in AI. Similarly, Microsoft’s 2024 Work Trend Index Report highlights that AI saves users time (90%), helps them focus on crucial tasks (85%), enhances creativity (84%), and boosts overall work satisfaction (83%).

‍

With Unframe’s Managed AI Delivery Platform, businesses experience measurable ROI faster, as the platform enables solutions to be built in days, not months. This rapid deployment means businesses can evaluate solutions and see value quickly. Additionally, because Unframe isn’t a point solution, the ROI can be seen in clearly targeted areas, not a general improvement in performance.

‍

Aligning AI with Business Objectives

The first step in measuring AI ROI is aligning the platform with specific business objectives. Without a clear linkage between AI capabilities and desired business outcomes, ROI calculations risk becoming abstract or misleading. Whether the goal is reducing operational costs, improving customer experience, increasing productivity, or boosting revenue, defining measurable objectives provides a baseline for evaluation and a benchmark for success. 

‍

Prioritizing Use Cases

Given the endless possibilities of AI, it is essential to prioritize use cases that align with the business’s primary goals. Starting with use cases that have a direct impact on key objectives ensures that the initial ROI measurements are meaningful and sets the stage for broader adoption. Learn more about some of the most impactful use cases for enterprises here.

‍

Metrics to Track for AI ROI

While traditional ROI metrics focus solely on financial returns, organizations need to track AI effectiveness across multiple dimensions - helping them achieve cost efficiency, revenue growth, and operational excellence.

‍

Below are the key metrics enterprises should consider:

‍

Cost Reduction

AI significantly reduces operational costs by automating manual tasks, streamlining processes, and minimizing errors.

‍

With Unframe, businesses can measure cost savings in terms of:‍

‍

• Labor Efficiency: Automate repetitive workflows, allowing teams to focus on high-value initiatives without increasing headcount.‍
• Operational Streamlining: Unframe’s AI solutions integrate seamlessly with existing systems to remove inefficiencies and reduce overhead costs.‍
• Error Mitigation: AI-powered insights help prevent costly human errors, improving accuracy in critical areas like compliance, data processing, and customer support.

‍

Revenue Growth

Unframe enables enterprises to unlock new revenue opportunities by leveraging AI-driven insights and automation.

‍

AI-powered capabilities can help organizations:‍

‍

• Personalize Customer Engagement: With AI-driven recommendations and intelligent agents, businesses can deliver hyper-personalized experiences that drive higher engagement and conversion rates.‍
• Optimize Sales Pipelines: AI insights provide sales teams with actionable data to prioritize leads and identify upselling opportunities effortlessly.‍
• Enhance Decision-Making: Unframe empowers organizations with proactive insights that help identify hidden revenue opportunities and refine go-to-market strategies. 

‍

Process Efficiency

Unframe’s AI solutions are designed to optimize business processes by improving speed, accuracy, and scalability across enterprise operations.

‍

Some key efficiency metrics include:‍

‍

• Reduced Cycle Times: AI streamlines processes across functions like observability, data abstraction, and modernization, allowing enterprises to operate more efficiently.‍
• Faster Decision-Making: With Unframe’s secure AI capabilities, businesses can analyze data from multiple sources instantly, leading to smarter, faster actions.‍
• Scalability Without Complexity: The platform enables enterprises to expand AI capabilities across functions without requiring costly model training or fine-tuning.

‍

Calculating Long-Term ROI

Measuring AI’s ROI requires a forward-looking approach. Unlike traditional ROI calculations, many AI benefits emerge as indirect gains over time. For example, productivity improvements may not immediately reduce headcount but can enable teams to handle a higher workload as demand grows. Early adopters of generative AI note that most immediate benefits manifest as productivity gains, which are leading indicators of future financial outcomes rather than direct revenue growth.

‍

What Sets High Performers Apart

The companies that are leading the way in AI adoption share some common characteristics:

‍

• Customized Solutions: High performers often develop proprietary AI models tailored to their unique needs rather than relying solely on off-the-shelf tools. This customization addresses specific business problems more effectively, creating a competitive advantage.
• Integrated Risk Management: These organizations embed risk management practices early in the AI development lifecycle, including bias checks, legal consultations, and designing auditable models.
• Cross-Functional Collaboration: Alignment across multiple departments such as: HR, legal, and finance in AI initiatives, ensuring broad-based support and alignment with organizational goals.

‍

Overcoming Challenges in Measuring ROI with Unframe

When measuring the ROI of AI, organizations often encounter obstacles:

‍

Viewing AI Projects in Isolation

According to PwC, a common mistake is treating each AI project separately instead of managing them as a portfolio. At Unframe, we build individual solutions that sit on top of our turnkey enterprise platform.

‍

Implementation Time

Deploying an AI platform typically requires significant time for integration with existing systems, data preparation, and model training. Unframe solutions are built and ready to be deployed in just hours. There is no model training or fine-turning needed. 

‍

Data Quality

AI models are only as good as the data fed into them. Poor-quality data can slow down the AI’s ability to generate value. Unframe’s ability to integrate with any system, allows you to combine all data sources into a single pane of glass. Leveraging your choice of LLM, keeps you in control and provides the highest data quality for your business.

‍

Learning Curve

AI platforms often require new skills, tools, and processes. Businesses must account for training staff and adjusting workflows to maximize the benefits of the AI solution. Unframe’s custom solutions make it simple to onboard. Users can do everything in natural language, leveraging total independence across the organization.

‍

Fragmented and Siloed Data

Many enterprises have critical data across disparate systems, such as ERP, CRM, Storage, Emails, Documents. This makes it difficult to assess AI’s impact. Unframe integrates seamlessly with any system (such as Salesforce, ServiceNow, Jira, etc.) with structured or unstructured data, and unifies it all through natural language. This centralized access enables end-to-end ROI tracking across cases and departments. Additionally, it leverages systems you’re already using, increasing their practically and ROI. 

‍

Short-Term Expectations versus Long-Term Value

Using different vendors and solutions for each AI tasks leads to duplicative costs, integration burdens, and data inconsistencies, making it difficult to measure any ROI. Unframe provides a single platform, no need to use multiple tools, for all use cases. Whether it’s enterprise search, vendor risk, IT observability, or contract management, there’s one platform, reducing overhead and offering a clearer picture of AI driven improvement.

‍

‍

Starting with a Proof of Value

To address concerns about AI ROI, Unframe offers a free proof of concept for your highest-priority use case. By integrating with your data sources, your team can experience the value of AI before committing to a full investment.

‍

Experience enterprise-grade AI that proves itself before you pay. Just tell us the use case. We’ll handle the rest. Book a demo here.