Enterprise software adoption faces structural friction because non-technical domain experts rarely think like software builders, according to an analysis by tech analyst Benedict Evans. While modern artificial intelligence enables users to generate custom tools or automate repetitive tasks without writing code, most professionals—such as lawyers or salespeople—focus on their core work rather than reimagining their workflows through software.
Evans notes that while products try to bridge this gap with templates and assistants, specialized enterprise tasks often require dedicated solutions or external intervention. This disconnect has driven demand for forward-deployed engineers who can identify automation opportunities within traditional organizations that internal staff overlook.
Furthermore, many underlying operational problems in large companies remain hidden or deeply embedded inside existing software systems like SAP and Workday. The analysis suggests that despite AI’s ability to lower the cost of tool creation, transforming business operations requires understanding non-obvious enterprise processes rather than relying solely on user-driven tool building.
Why it matters
Founders must build specific, domain-aware workflows rather than expecting non-technical end users to prompt their own AI tools.
Enterprise AI startups may need forward-deployed services teams to uncover hidden automation opportunities inside customer operations.
Investors should evaluate AI products on deep process integration rather than low-code generative capabilities alone.
Source: ben-evans.com
