Top KPIs for AI Transformation Projects

AI is a big investment, and to make sure you’re getting the most out of it, you need concrete ways to measure its benefits. What metrics can demonstrate AI’s impact on the productivity of your company?

While each company may have different goals, here are some KPIs that can help you assess how thoroughly you’ve implemented AI in your organization and metrics that can help you maximize the ROI of your AI transformation efforts. 

Metrics for Better Compliance and Governance With AI

Compliance and governance is an area where AI is a massive help, especially for companies in regulated industries like finance, life sciences and healthcare. Some KPIs that will help companies benchmark their compliance, regulatory and governance efforts include: 

• Assessing adherence to standards like GDPR, HIPAA and industry-specific regulations
• Establishing more transparent, auditable processes to address compliance concerns and creating automated reporting and documentation (for example, in the healthcare insurance industry, the American Academy of Professional Coders, or AAPC, usually requires a minimum of 90 percent coding accuracy for most audit types)
• Measuring the effectiveness of policies for secure and compliant data usage in AI models

KPIs for Measuring Productivity and Operational Efficiency

 AI can help companies skyrocket their productivity rates and their operational efficiency. Here are some KPIs to ensure you’re getting more out of your resources with AI: 

• Quantifying process automation rates, or the rates of tasks automated or optimized by AI across functions. Forbes estimates that about 45% of tasks in the average company can be automated.
• Tracking time savings. AI can measure reductions in time spent on repetitive or manual processes. Thomson Reuters estimates AI should be saving each employee about four hours of work per week. Bain & Company estimates that AI will help software engineering become 15% to 30% more productive, while HR teams should see a 40% drop in the time needed to write a job posting when using AI.
• Optimizing model performance by having AI track accuracy and efficiency of large language models in achieving specific business outcomes. 

Metrics for Improving Security and Risk Management

AI can improve your security and lower your risk of issues. You can measure your AI transformation progress in relation to security with metrics such as:

• Incident response time. Monitor how quickly AI systems detect and respond to security threats. As AI progresses, the average dwell time and incident response times should be down to minutes. 
• Vulnerability management. Track the frequency and resolution of security vulnerabilities in AI applications.
• Oversight metrics. Evaluate how well AI solutions provide control and visibility over data and applications.

KPIs for Measuring Financial and Budgetary Progress

Many companies invested in AI transformation with the main goal of increasing their bottom line. Make sure you’re getting a healthy ROI on your AI transformation projects and increasing your company’s profit margins by measuring:

• Cost predictability. To keep companies profitable, they need to monitor adherence to budget forecasts and predictable spending. AI can monitor your finances to keep you on track. Additionally, owning your AI platform will help you keep your costs predictable, rather than relying on third-party vendors that can increase their prices anytime. 
• Cost efficiency. AI can help identify areas where you can cut costs, negotiate vendor contracts for better rates and many other ways of helping with cost efficiency. About 36% of financial services professionals reported that AI decreased their company’s annual costs by more than 10%. 
• Total cost of ownership (TCO). Your AI TCO can be much cheaper when you own your AI platform because you can avoid vendor lock-in, you don’t need expensive licenses, it’s easier to scale on your own and you don’t have to pay for any features you aren’t using. 

KPIs for Innovation and Future-Proofing Your Company

Simply implementing AI is not going to keep you competitive. You’ll need to keep finding ways to make AI work for your company. To keep your momentum, here are some KPIs for benchmarking innovation and future-proofing your company: 

• AI adoption maturity. Evaluate how advanced the organisation is in adopting and optimizing AI.
• Innovation pipeline. One KPI to help you keep your finger on the pulse of innovation is the number of new AI-driven projects initiated after transformation. According to AIPRM, programming teams that used AI coded more than double the projects per week than non-users. The more AI-driven projects you have, the more you can accomplish and hit innovations ahead of competitors. 
• Adaptability. Assess how well AI systems respond to new business challenges or technological advancements. Companies can future-proof themselves by using AI to identify patterns and trends in real-time and make quick, data-driven decisions to adjust to changing market conditions.

Achieve Your AI Transformation KPIs with SUSE 

SUSE’s enterprise generative AI platform can help your company achieve your AI transformation goals, while ensuring your control and ownership. Future-proof your AI investments by building custom AI applications on a trusted platform.

As your company undergoes AI transformation, you can better understand the benefits of AI by reading our blog, “Generative AI Platforms in the Enterprise: Key Benefits, Use Cases and Trends.”