At Rise of AI 2019 in Berlin, Michael Brehm, founder and managing director of i2x, argues that AI should augment human workers rather than replace them, using his company's real-time conversation analytics for telesales and service agents as the example. He traces the idea to his previous company, rebate networks, where 2,500 of 10,000 employees were telesales agents he struggled to manage. Citing OECD data, he argues the common fear that automation destroys jobs is backwards: countries with more robots and technology have lower unemployment, not higher, contradicting 1990s predictions. He argues the real risk is not job loss but a widening gap between high-tech nations, which benefit from automation, and developing nations that lose the path of industrializing through basic manufacturing. Brehm describes how i2x records and analyzes every sales or service call in real time, using its own speech recognition, to give agents, team leads and managers actionable feedback during, not after, a call, arguing this keeps underperforming-but-trainable agents in their jobs rather than having them let go.
Key takeaways
- Michael Brehm cites OECD data showing more robots and automation correlate with lower unemployment across countries, not higher.
- He argues the bigger economic risk of AI is a widening gap between high-tech nations and developing nations that lose the path to industrialize through basic manufacturing.
- i2x records and analyzes every sales or service call in real time using its own speech recognition, giving agents feedback during the call rather than after.
- He says i2x's product requires buy-in from agents, supervisors and managers together, not a tool tailored to just one group.
- He argues full call automation remains risky because deviations from expected interactions can cause brand damage that outweighs savings.
Detailed notes
Origin: a concrete business problem in telesales
Michael Brehm explains he wanted to build software that helps people communicate better, and traces the idea to his previous company, rebate networks, which grew to 10,000 employees in 30 countries before being sold in parts to Google and Amazon and taken public. Of those, 2,500 were telesales agents who, he says, "drove me crazy" by not following instructions, making sales and customer support a concrete, high-value starting point because companies close to revenue would pay for a solution.
Why "no more jobs" is backwards
Brehm argues that despite constant predictions of an AI-driven jobs crisis, the actual crisis today is reversed: there are more jobs than people to fill them. He cites OECD data showing a correlation across countries between more robots and automation and lower, not higher, unemployment, directly contradicting 1990s predictions that robots would cause mass unemployment. He challenges two assumptions behind the fear: that the total amount of work is fixed (he argues sectors like hospitals and nursing homes have far more work than capacity), and that human intelligence and capability will stay at their current level rather than continuing to evolve through augmentation, bionics or gene editing.
Winners and losers: high-tech nations versus developing nations
Brehm predicts more AI leads to higher productivity and more jobs overall, but argues the real winners will be high-tech nations while the losers will be developing nations that have not yet reached the current level of industrialization, because automating basic production such as clothing manufacturing removes the path by which those countries historically industrialized, widening the gap between developed and developing nations.
How i2x analyzes calls in real time
Brehm contrasts the old model of customer communication, where companies could randomly monitor and give feedback on only one to three percent of calls, with i2x's approach of recording and analyzing every call using its own automatic speech recognition system, breaking calls into data points and feeding real-time coaching back to the agent during the call, when it can still be acted on. He stresses that value requires buy-in from three groups together: agents, team leads/supervisors, and managers, since supervisors are freed from listening to bad calls all day and managers get real-time KPIs for fact-based management. He cites a claim that over 40 percent of service and sales staff who quit say they did so because they received too little training.
Q&A highlights
Asked about handling dialects such as Austrian German, Brehm says it is an economic decision: most companies prioritize building for English or standard German rather than smaller dialect or language markets, so smaller-language requests currently have to be turned down. Asked about differentiation against better-capitalized competitors like Google, he argues focused startups tend to beat one-size-fits-all incumbent solutions because large companies spread limited attention across many projects, and that i2x's moat comes from collecting highly specialized data in narrow use cases over time. Asked whether full call automation is the logical next step, Brehm says it is possible but risky, since even small deviations from expected interactions can trigger brand damage that outweighs automation savings, and argues service is shifting from a cost center to a differentiator, making well-supported human agents more valuable, not less.
Quotes
The true winners are the high tech nations and the really big losers I think will be the third world countries.
Michael Brehm
More AI, higher productivity, more jobs.
Michael Brehm
We help people to keep their jobs and actually not to replace them because we augment.
Michael Brehm
Questions answered in this talk
Does more automation and robots lead to more unemployment?
According to Michael Brehm at Rise of AI 2019, OECD data shows the opposite correlation across countries: more robots and technology adoption correlate with lower unemployment, not higher.
How does i2x help call center agents improve in real time?
Michael Brehm explains at Rise of AI 2019 that i2x records and analyzes every call with its own speech recognition system and sends actionable coaching feedback to agents during the call, rather than only reviewing a small sample of calls after the fact.
Who benefits most and least from AI-driven automation, according to Michael Brehm?
At Rise of AI 2019, Brehm argues high-tech nations benefit most, while developing nations lose out because automating basic manufacturing removes the industrialization path those countries have historically relied on.