AI Assessment & Advice: Optimizing Technology Stack Efficiency

Managing a company's technology stack efficiently presents a significant challenge for many organizations. This task is often handled by a dedicated internal team or, more frequently, by external consulting companies, incurring substantial costs. Fragmented technology stacks, characterized by overlapping features and disconnected data, are difficult to manage effectively. Ensuring that each tool integrates seamlessly into the broader business strategy and delivers a positive return on investment can also be a struggle. Managing thousands of configuration settings manually across numerous SaaS applications is time-intensive and prone to errors, while configuration drift can create security vulnerabilities. Furthermore, excessive user privileges and orphaned accounts within the technology stack increase the risk of insider threats.

Data reveals a widespread issue of underutilized software and inefficient technology spending in businesses. On average, 33% of SaaS spend is wasted due to underutilization. Some studies indicate that businesses underestimate their software usage by as much as 40%. Organizations with 100 to 200 employees waste an average of $89,033 (34%) of their software budget, and this figure rises to a staggering 48% for companies with over 200 staff. Moreover, 44% of Microsoft Office 365 licenses are reported as 'underutilized or oversized', and nearly one-third (29%) of all SaaS software spend is wasted. On average, only 45% of company-provided applications are used regularly, and organizations spend approximately $49 million annually on SaaS.

Artificial intelligence offers powerful capabilities for identifying bottlenecks and inefficiencies in technology usage. AI algorithms can analyze vast amounts of data to detect patterns and anomalies in how technology is being used. Machine learning can pinpoint underutilized or overutilized resources, while AI can analyze log data to identify recurring errors or indicators of slow performance. AI-powered tools can continuously monitor application performance, detecting deviations from established baselines. These analytical capabilities enable AI to help optimize resource allocation and improve capacity planning, leading to a more efficient technology stack.

Arfiti's 'AI Assessment & Advice' features are specifically designed to address these challenges. By identifying bottlenecks in technology usage through the analysis of usage patterns and performance metrics, Arfiti helps businesses manage their technology stack more efficiently. The platform pinpoints technical inefficiencies, enabling the reduction of wasted technology spending and the optimization of resource allocation, thereby tackling the problem of underutilized software. Arfiti's 'AI Assessment & Advice' provides concrete improvement opportunities based on data analysis, guiding businesses towards a more streamlined and effective technology environment. Furthermore, the technology stack evaluation feature assists businesses in making informed decisions about their software investments, potentially reducing their reliance on expensive external consulting services.