Forbes Technology Council: AI Made Enterprise Software Cheaper To Prove

Prospects used to ask Euvic US whether an idea was worth building. Now many of them arrive with a prototype built in days and ask whether the team can make it real.

Tobias Fischer, Vice President of Marketing at Euvic US, breaks down that shift in a new Forbes Media Feature for the Forbes Technology Council.

Where The Savings Landed

Two years ago, the common expectation held that cheaper code would shrink the engineering market. The U.S. Bureau of Labor Statistics now projects 10% growth in employment for software developers, QA analysts, and testers from 2025 to 2035, and Gartner forecasts worldwide IT spending of $6.37 trillion in 2026, up 14.2%.

Tobias reads this through Jevons paradox: when something gets cheaper to use, people use more of it. In his telling, the savings landed on the justification stage, the months of committee work that kept projects in the “someday” column for years.

The Pipeline Still Has Slow Stages

AI sped up one stage of the delivery pipeline. Faros research covering 22,000 developers found task throughput up about 34% on teams with high AI adoption, while code review time grew fivefold and incidents per change tripled. DX's longitudinal study puts the average gain in engineering output near 10%.

Delivery moves only as fast as its slowest stage."

Tobias Fischer

Vice President of Marketing

Verification adds work of its own. On our own projects, we have seen a 50-page AI-written spec nobody could check before the build, and a design that cost up to $2,000 in AI spend before a late requirements change got it thrown out. Security widens the gap, since Veracode found that 45% of AI code-generation tasks introduced a vulnerability.

Team Structure Sets The Result

Google's 2025 DORA report describes AI as an amplifier that strengthens teams with good practices and exposes those without them. The teams getting more from AI put every role in one unit, use AI at every step, and give one person ownership of quality and AI spend. On one full build, a team organized this way delivered about 50% more than a traditional team with the same scope and headcount, based on our internal project data.

What Buyers Want De-Risked Now

Polished websites and case studies now take an afternoon to produce, so every vendor looks capable at first glance. Gartner found that 67% of B2B buyers prefer a rep-free experience, which means they judge firms with less contact. MIT research reported by Fortune found that AI initiatives built with specialized partners succeeded about 67% of the time, while internal builds succeeded about a third as often.

What This Means For Euvic US Marketing

For us, the work now is de-risking the build. Prospects want to know we have taken an application from prototype to live, at a scale where millions of people will eventually use it, and through real security reviews.

That has changed how Tobias works. He spends more time with our delivery teams, sits in project reviews, and asks engineers what nearly went wrong and how they caught it. Those details are the ones a prospect cannot find anywhere else.

Our delivery teams are the main source of our content now, because their stories are the one thing a competitor cannot copy."

Tobias Fischer

Vice President of Marketing

Each proof point we publish ties to a named engineer, a specific decision, and an outcome we can verify. When every vendor can publish the same polished content, evidence from people who have done the work before is what stands out. Readers who want to see that evidence in practice can browse our case studies or learn how we apply AI across delivery through SDLC with AI.

Read The Full Article

The complete article, including the research behind each figure, is on Forbes: AI Made Enterprise Software Cheaper To Prove. Here's How I'm Adapting As A Marketing Leader