AI After the Hype: How Roles and Organizations Are Changing Today

By the figures Julien Look shows, 88 percent of people now use AI at work, yet only 5 percent of AI projects deliver measurable value, counted in EBIT. The software engineer, who consults on AI adoption, spends his talk on that gap. His answer: it is rarely a technology problem. It is change management, and it starts at the top.

What the talk covers

• Where adoption stalls: little C-level involvement (2 percent in Germany, according to his slides), middle managers who aren't prepared (23 percent feel ready), and teams that distrust agent output because nobody can trace each step.
• Why transformation takes years, not six months, and why he suggests pitching clients a retention contract of around five years.
• How to build buy-in from the bottom: raise awareness and desire before you introduce a tool, and set up AI champions. A group of 7 to 10 works, bigger groups turn passive. Large companies get several small local groups plus one center of excellence.
• How roles change: people without a coding background now build apps, designers ship UI, and a SaaS team of three can be enough.
• Two examples: Bosch's large legacy ERP migration (align first, then upskill, then clean up the core system; developers about 20 percent more productive), and "strategy as protocol", where the strategy is documented in a form that people and AI can read.

Three questions before you pitch a transformation project

1. Who owns this? If it isn't the executive level, rethink it.
2. What does success look like in 90 days, and in one year?
3. What do you want to change, and which bottleneck are you solving? "We want AI" is not an answer.

His practical tip: draw a process map together with the leadership.

Q&A

How to handle clients who want AI for nonsensical use cases, how to find AI champions (pre-select, then ask who wants to join) and how to assess a company's culture (a workshop, then one micro project in the biggest bottleneck).

Who it's for

Consultants and freelancers who sell or run AI projects inside companies.